If you want to participate in the analytics breakout group you may want to download Gephi (https://gephi.org/) on your laptop ahead of time. (One caveat though: if your laptop is slow or not so powerful you may not be able to run Gephi.)
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We’re aware that the changes to the Instagram API has greatly changed our ability to do research since we pitched this workshop.
Because we anticipate questions about the API changes, we’ve shifted the focus of the workshop to account for that.
Here’s a brief outline of the workshop:
A note on breakout groups
Depending on where the API breakout group takes the discussion, you may want to bring your laptop to try out some code.
If you want to participate in the analytics breakout group you may want to download the software on your laptop ahead of time. One caveat though: if your laptop is slow or not so powerful you may not be able to run Gephi.
The ethics of Instagram breakout group will be a discussion group, so no tech is required.
We look forward to seeing you!
Jess, Andreas, Samantha and Andy
AdIf you want to participate in the analytics breakout group you may want to download the software on your laptop ahead of time. One caveat though: if your laptop is slow or not so powerful you may not be able to run Gephi.
Welcome to this workshop. To participate, please make sure you bring your own laptop so that we can work through a number of hands-on exercises.
You will also need to install a trial version of Tableau Desktop (http://www.tableau.com/products/trial) ahead of time, and download the following data file from Dropbox: https://www.dropbox.com/s/o2afy089xbb2kpd/Paris%20Climate%20Change%20Conference%202015.twbx?dl=0
Workshop Contact
Axel Bruns - a.bruns@qut.edu.au
Location: PSH (Professor Stuart Hall Building) - 314
Goldsmiths, University of London, Building 2
Campus Map
Presenters:
The workshop will provide an overview of critical themes to be covered in the Sage Handbook of Social Media Research Methods to be published in 2016. The Handbook is the first book to cover not only the entire research process in social media research from question formulation to the interpretation of research findings, but also to include specific chapters and examples on how data collection and analysis takes place on specific social media platforms such as Twitter and Instagram.
The workshop will focus on a critical theme that weaves through the entire handbook, namely the tensions and controversies that have emerged around two fundamental different approaches toward the study of social media: big data vs. small data. Three central themes will be explored in an interactive format that includes a live poll and feedback from the audience:
All workshop participants will get gratis access to DiscoverText for the remainder of 2016. DiscoverText is designed specifically for collecting and cleaning up messy Twitter data streams. Use basic research measurement tools to improve human and machine performance classifying Twitter data over time. The workshop covers how to reach and substantiate inferences using a theoretical and applied model informed by a decade of interdisciplinary, National Science Foundation-funded research into the text classification problem.
Participants will learn how to apply “CoderRank” in machine-learning. Just as Google said not all web pages are created equal, links on some pages rank higher than others, Dr. Shulman argues not all human coders are created equal; the accuracy of observations by some coders on any task invariably rank higher than others. The major idea of the workshop is that when training machines for text analysis, greater reliance should be placed on the input of those humans most likely to create a valid observation. Texifter proposed a unique way to recursively validate, measure, and rank humans on trust and knowledge vectors, and called it CoderRank.
Pre-Workshop Prep:
No Prerequisites Required
Workshop Contact
Stu Shulman - stu@texifter.com
Welcome to this workshop. To participate, please make sure you bring your own laptop so that we can work through a number of hands-on exercises.
You will also need to install a trial version of Tableau Desktop (http://www.tableau.com/products/trial) ahead of time, and download the following data file from Dropbox: https://www.dropbox.com/s/o2afy089xbb2kpd/Paris%20Climate%20Change%20Conference%202015.twbx?dl=0
Workshop Contact
Axel Bruns - a.bruns@qut.edu.au
Location: PSH (Professor Stuart Hall Building) - 314
Goldsmiths, University of London, Building 2
Campus Map
Presenters:
The workshop will provide an overview of critical themes to be covered in the Sage Handbook of Social Media Research Methods to be published in 2016. The Handbook is the first book to cover not only the entire research process in social media research from question formulation to the interpretation of research findings, but also to include specific chapters and examples on how data collection and analysis takes place on specific social media platforms such as Twitter and Instagram.
The workshop will focus on a critical theme that weaves through the entire handbook, namely the tensions and controversies that have emerged around two fundamental different approaches toward the study of social media: big data vs. small data. Three central themes will be explored in an interactive format that includes a live poll and feedback from the audience:
All workshop participants will get gratis access to DiscoverText for the remainder of 2016. DiscoverText is designed specifically for collecting and cleaning up messy Twitter data streams. Use basic research measurement tools to improve human and machine performance classifying Twitter data over time. The workshop covers how to reach and substantiate inferences using a theoretical and applied model informed by a decade of interdisciplinary, National Science Foundation-funded research into the text classification problem.
Participants will learn how to apply “CoderRank” in machine-learning. Just as Google said not all web pages are created equal, links on some pages rank higher than others, Dr. Shulman argues not all human coders are created equal; the accuracy of observations by some coders on any task invariably rank higher than others. The major idea of the workshop is that when training machines for text analysis, greater reliance should be placed on the input of those humans most likely to create a valid observation. Texifter proposed a unique way to recursively validate, measure, and rank humans on trust and knowledge vectors, and called it CoderRank.
Pre-Workshop Prep:
No Prerequisites Required
Workshop Contact
Stu Shulman - stu@texifter.com
Challenging Social Media Analytics
Abstract
This talk explores social media analytics as an emergent field of sociotechnical practice. Situated in the wider ‘data deluge’ social media data have drawn the attention of a wide range of academic researchers, policy makers and businesses, attracted by the promise that they appear to carry of new insights into the social world. However, initial explorations of the opportunities in these data are beginning to reveal some significant methodological challenges in working with social media data and these – in turn – challenge some of the early approaches to and claims made from them. This talk works this claim through a local history of social media data research, specifically Twitter analytics, to suggest how we might now push forward from initial optimism and subsequent critique into a new phase of research that makes the most of these data through new assemblages of research practice.
Bio
Susan Halford is Professor of Sociology and a Director of the Web Science Institute both at the University of Southampton, UK. A Geographer by training and an organizational sociologist for many years, her recent research focusses on the politics of digital data and artefacts, with particular attention to questions of method and expertise. Susan is partiularly interested in how computational processes shape the curation of digital data and has recently explored this along two dimensions (1) the impact of computational processes on knowledge - what can be known, by whom and how - and, in turn, the implications for expertise and the future of academic disciplines (see for example Halford et al 2013 Digital Futures: sociological challenges and opportunities in the emergent semantic web); and (2) the question of data provenance and applied methods of data analysis, specifically in relation to social media data (see Tinati et al 2014 Big Data: methodological challenges and approaches for sociological analysis). Throughout her work Susan is concerned to harness sociological critiques of digital data and infrastructures to develop constructive and progressive engagement between the social and computational sciences. She is also actively involved in current debates around the ethics of big data, particularly social media data and is currently chairing the revision of the 'digital sociology' ethics guidelines for the British Sociological Association.
Background:
Discussion online of illicit drug taking can be seen as a knowledge sharing that creates a sense of shared community for drug users, which can lead to harm reduction and also offers social resistance to mainstream drug-use narratives (Bancroft & Reid, 2016; Barratt, Allen & Lenton, 2014). Online drug discussion and the communities of interest formed through that discussion have been common in Australia for at least twenty years. As internet communication technologies have changed during this time, so too have the ways in which that discussion occurs. Recent developments in social media therefore have created new socio-technical forms for online drug discussion. This study will focus on online public discussion via social media platforms (such as Twitter) about the recent provisions for legal supply of medicinal cannabis in Australia. Through the specific focus of this study on an illicit drug with recently legalised supply and access avenues, we seek to reduce possible harms to the online drug discussion community yet retain the benefits of studying how a stigmatised topic such as illicit drug use is engaged with through social media.
Objective:
The aim of this research is to investigate whether and how social media is used to debate, amplify and curate discussion of illicit drugs online using a case study of recently legalised supply and access of an illicit drug. The second objective is the development of insights into the specific benefits to research of big data analytical approaches to social media that contributes insights into the online public debate of controversial topics.
Methods:
The study will seek to characterise the communications network (including bots) of those who are commenting, curating and listening to this discussion. To do this, we will conduct the analysis within the Australian twittersphere using social media data curated by the Tracking Infrastructure for Social Media Analysis (TrISMA) archive. Through the use of Tableau, we will initially identify the communications network of those engaging with the topic of “medicinal cannabis”, associated hashtags (such as #medicinalcannabis, #cannabis, #marijuana, #MedicalMarijuana), and public figures and organisations, during key events leading up to and including the recent provisions for legal supply of medicinal cannabis in Australia. The analysis will then focus on developing a typology of actors characterised by: attempts at dominance (through frequency and volume of commenting); influence and amplification (through the dispersion of messages by retweets, quoting and modified tweets); and content curation (tweet streams that consistently reflect particular positions and paradigms in the debate).
Results:
This research seeks to generate insight into how social media engagement contributes to the ways in which Australians discuss the complex social issues relating to drug use, focusing on a ‘liminal’ case of the legalisation of a normally illicit drug for specific medical purposes’
Future Work:
This study will contribute to the rationale and generation of social media analysis of illicit drug discussion online. For future work, it will outline how the mechanisms for and configurations of social engagement, influence and information dissemination identified through this case study can contribute new knowledge of social change processes through big data analytical approaches to social media.
References:
Bancroft, A., & Scott Reid, P. (2016). Challenging the techno-politics of anonymity: the case of cryptomarket users. Information, Communication & Society, 1-16. doi: 10.1080/1369118x.2016.1187643
Barratt, M. J., Allen, M., & Lenton, S. (2014). ‘PMA sounds fun’: Negotiating drug discourses online. Substance Use and Misuse, 49, 987-998.
Background:
As digital and social technologies have come to shape the city and the daily lives of its citizenry, it is timely and necessary that the means by which we envision the future city is enabled by these same technologies. The changing nature of the city in the digital age, the availability of rich GIS data sets, social media networking platforms, and open source online collaborative virtual worlds, suggest that a key challenge in achieving greater citizen engagement and participation in urban planning decisions is how to best leverage both the social and technological opportunities implicit in these conditions. This Work-in-Progress paper discusses first results from a SSHRC funded project, Virtual Hamilton, which integrates the design, testing and implementation of a publicly accessible, user-friendly community planning and visualization system. The Virtual Hamilton project also aims to integrate community knowledge contribution via multiple social media tools, such as Twitter and Instagram with an open source virtual environment for city modeling.
Objective:
The Virtual Hamilton project goal is to explore novel techniques and approaches for integrating a 3D visualization platform and interactive social media for the purposes of civic engagement in community development and participatory urban planning processes. By integrating both cutting-edge High-Performance-Computing (HPC) technologies with social sciences theories and methods, the project aims to provide novel insights on the use of digital technologies to facilitate public engagement and participation in city planning.
Methods:
The project follows an interaction design methodology (Preece et al., 2002), integrating different methods (mixed methods approach) at specific stages of the project (see Figure 1 below). In the first phase, we conducted 12 expert interviews with professional planners and 3 focus group studies to access diverse stakeholder opinions. We also staged two 100 attendee participatory planning charrettes, jointly hosted by the City of Hamilton and McMaster and Ryerson University partners. We are now in the process of evaluating and analyzing the different outcomes, which will then inform our user studies of the first prototype of the 3D virtual planning environment.
Results:
Initial analysis of the expert interviews and focus groups indicate that while participatory planning has been readily adopted as a value by municipal authorities and planning professionals, it has not been successfully implemented. Problems cited by professionals include the increased costs and workload to facilitate public participation, planning knowledge deficits on the part of the lay participants. Lay participants and business operators cited a lack of information from planning authorities and professionals and the offer of token, rather than meaningful, planning engagement. All participants, including charrette participants, responded positively to the virtual planning environment, requesting ongoing access to the environment and suggesting extended application to other planning sites and issues.
Future Work:
Future work includes detailed analysis of the data and conducting a user study of the virtual environment for participatory urban planning.
References:
Preece, J., Rogers, Y., and Sharp, S. (2002). Interaction design: Beyond human-computer interaction. New York, NY: J. Wiley & Sons.
Background:
Social media have not only changed the way people interact in their everyday lives but have also entered academia. Researchers are starting to use general social media platforms (e.g., Twitter, Facebook) as well as specialized tools (e.g., ResearchGate, Mendeley) for the creation, management and dissemination of scholarly work. The adoption of social media by scholars faces a variety of facilitators and barriers. Known obstacles include lack of time, lack of recognition of social media activities for getting a promotion or funding, and information overload (Acord & Harley 2013; CIBER 2010; Gruzd, Staves, & Wilk 2012; Nicholas et al. 2011; Ponte & Simon 2011), while uptake is facilitated by peer influence and collaborating with scholars from other institutions (Acord & Harley 2013; CIBER 2010; Gruzd, Staves, & Wilk 2012; Procter et al. 2010). It varies across disciplines and age or level of career progression (CIBER 2010; Gruzd, Staves & Wilk 2011, 2012; Holmberg & Thelwall 2014; Nicholas et al. 2014; Pearce 2010; Procter et al. 2010; Van Noorden 2014). Maintaining or creating ties with other scholars, promoting and disseminating their research, staying informed, communicating with other scholars and sharing information (CIBER 2010; Gruzd & Goertzen 2013; Gruzd, Staves, & Wilk 2012; Nicholas et al. 2014; Pearce 2010) were identified as main motivations of scholarly social media use.
Although collaboration is essential for science and has been associated with higher impact (Larivière et al. 2015; Sonnenwald 2007), the link between social media use and collaborative research practices remains largely unexplored.
Objective:
The objective of our study is to examine how scholars use social media at different stages of the research process in the context of an inter-institutional collaborative research project. More specifically, the study aims to:
(1) provideanin-depthanalysisofusepracticesofsocialmediaateachstageofaninter-institutional collaborative research project; and
(2) explorethefactorsofadoptionofsocialmediabyteamsofresearchersininter-institutional collaborative research projects.
Methods:
A mixed-methods sequential exploratory design (Creswell & Plano Clark 2011) will be used. The first phase will consist in a multiple case study. Four to eight inter-institutional research teams from various disciplines will be selected. The results of in-depth interviews conducted with each team member will be combined with quantitative bibliometric and altmetric data in order to provide a rich and contextualized description of the individual and collective factors that affect the adoption–or non-adoption—of social media in this context. The results of this first phase will inform the second phase consisting in a Canada-wide survey of researchers, allowing for a more complete picture of the phenomenon under study.
Results:
The project is still in its early stages. Initial efforts were devoted to defining the theoretical framework. To understand why and how a team of researchers use social media, we examined prominent technology adoption models—the Diffusion of Innovation Theory (Rogers 1983), the Technology Acceptance Model (TAM) (Davis 1989), and the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al. 2003)—as well as models focusing on work teams—the Adaptive Structuration Theory (AST) (DeSanctis & Poole 1994) that outlines the factors influencing technology appropriation by groups within an organization, and Constantine’s (1993) organizational reference paradigms that outlines the characteristics of four different group “personalities”. To these, we added the Theory of Information Sharing of Constant, Keisler and Sproull (1994), enriched by Jarvenpaa and Staples (2000), which will allow us to better understand the collaborative personality of each team member, in the context of a specific research team, something that is not included in traditional technology adoption models.
Future Work:
In order to complete the first phase of our research, the next steps will be to define the selection criteria for the multiple case study, and then recruit research teams that have received funding from a Canadian research
References:
Acord, S. K., & Harley, D. (2013). Credit, time, and personality: The human challenges to sharing scholarly work using Web 2.0. New media & society, 15(3), 379-397. doi: 10.1177/1461444812465140
CIBER. (2010). Social media and research workflow. London: London’s Global University. Retrieved from http://ciber-research.eu/download/20101111-social-media-report.pdf
Constant, D., Kiesler, S., & Sproull, L. (1994). What’s mine is ours, or is it? A study of attitudes about information sharing. Information Systems Research, 5(4), 400-421. doi: 10.1287/isre.5.4.400
Constantine, L. L. (1993). Work organization: Paradigms for project management and organization. Communications of the ACM, 36(10), 35-43.
Creswell, J. W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research (2nd ed.). Los Angeles: SAGE Publications.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. doi: 10.2307/249008
DeSanctis, G., & Poole, M. S. (1994). Capturing the complexity in advanced technology use: Adaptive structuration theory. Organization Science, 5(2), 121-147. Retrieved from http://www.jstor.org/stable/2635011
Gruzd, A., & Goertzen, M. (2013). Wired academia: Why social science scholars are using social media. In Proceedings of the 46th Hawaii International Conference on System Sciences (HICSS) (pp. 3332-3341). doi: 10.1109/HICSS.2013.614
Gruzd, A., Staves, K., & Wilk, A. (2011). Tenure and promotion in the age of online social media. Proceedings of the American Society for Information Science and Technology, 48(1), 1-9.
Gruzd, A., Staves, K., & Wilk, A. (2012). Connected scholars: Examining the role of social media in research practices of faculty using the UTAUT model. Computers in Human Behavior, 28(6), 2340-2350. doi: j.chb.2012.07.004
Holmberg, K., & Thelwall, M. (2014). Disciplinary differences in Twitter scholarly communication. Scientometrics, 1-16. doi: 10.1007/s11192-014-1229-3
Jarvenpaa, S. L. et Staples, D. S. (2000). The use of collaborative electronic media for information sharing: An exploratory study of determinants. Journal of Strategic Information Systems, 9, 129-154.
Larivière, V., Gingras, Y., Sugimoto, C. R., & Tsou, A. (2015). Team size matters: Collaboration and scientific impact since 1900. Journal of the Association for Information Science and Technology, 66(7), 1323- 1332. doi: 10.1002/asi.23266
Nicholas, D., Watkinson, A., Rowlands, I., & Jubb, M. (2011). Social media, academic research and the role of university libraries. The Journal of Academic Librarianship, 37(5), 373-375.
Pearce, N. (2010). A study of technology adoption by researchers. Information, Communication & Society, 13(8), 1191-1206. doi: 10.1080/1369118100366360
Ponte, D., & Simon, J. (2011). Scholarly communication 2.0: Exploring researchers’ opinions on Web 2.0 for scientific knowledge creation, evaluation and dissemination. Serials Review, 37(3), 149-156.
Procter, R., Williams, R., Stewart, J., Poschen, M., Snee, H., Voss, A., & Asgari-Targhi, M. (2010). Adoption and use of Web 2.0 in scholarly communications. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 368(1926), 4039-4056.
Rogers, E. M. (1983). Diffusion of innovations. New York: Free Press.
Sonnenwald, D. H. (2007). Scientific collaboration. Annual Review of Information Science and Technology, 41(1), 643-681. doi : 10.1002/aris.2007.1440410121
Van Noorden, R. (2014). Online collaboration: Scientists and the social network. Nature, 512(7513), 126-129.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478.
Background:
When participating online, individuals draw on the limited cues they have available to create for themselves an imagined audience (Litt, 2012). Such audiences shape users’ social media practices, and thus the expression of identity online (Marwick & boyd, 2011). While institutions encourage scholars to go online (Mewburn & Thompson, 2013), and many scholars perceive value in online networks themselves (Veletsianos, 2016), limited research has explored the ways that scholars conceptualize online audiences.
Objective:
In this research we posed the following questions: (1) how do scholars conceptualize their audiences when participating on social media, and (2) how does that conceptualization impact their self-expression online? By answering these questions, we aim to provide a more nuanced picture of scholars’ social media practices and experiences.
Methods:
We employed a qualitative approach to this study. We recruited participants through a variety of methods: invitations to participate via email, through postings on blogs and social media, and through snowball sampling. From 42 responses, we selected 16 participants who represented a range of academic disciplines and roles (mean age = 41.6; S.D = 8.1; 12 self-identified as female, 3 as male, and 1 as transgender). Data were generated from two sources: semi-structured interviews with each participant, and examination of the social media spaces they used (e.g. blogs, Facebook, Twitter). Data were analyzed using the constant comparative approach (Glaser & Strauss, 1967). In particular, as we read a piece of data (e.g., a sentence, a paragraph) we assigned codes to indicating perceived audiences and impacts on expression of identity. Next, new data (e.g., another paragraph), were either assigned one of the pre-existing codes or assigned a new code that was created to describe the data. When new codes were created, data are re-read to examine whether the new codes could be assigned to them. Eventually, the process of constantly comparing codes and data lead to a list of codes describing the data, which were compiled into themes.
Results:
Participants identified four specific groups as composing their social media audiences: (1) academics, (2) family and friends, (3) groups related to one’s profession, and (4) individuals who shared commonalities with them. Interviewees felt fairly confident that they had a good understanding of the people and groups that made up their audiences on social media, but distinguished their audiences as known and unknown. The known audience included those groups and individuals known to interviewees personally. The unknown audience consisted of members whom participants felt they understood much about but did not know personally. Interviewees reported using their understanding of their audience to guide their decisions around what, how or where to share information on social media. All participants reported filtering their social media posts. This action was primarily motivated by participants’ concerns about how postings would reflect on themselves or others.
Implications:
The audiences imagined by the scholars we interviewed appear to be well defined rather than the nebulous constructions often described in previous studies (e.g. Brake, 2012; Vitak, 2012). While scholar indicated that some audiences were unknown, none noted that their audience was unfamiliar. This study also shows that a misalignment exists between the audiences that scholars imagine encountering online and the audiences that higher education institutions imagine their scholars encountering online. The former appear to imagine finding community and peers and the latter imagine scholars finding research consumes (e.g., journalists).
References:
Brake, D. R. (2012). Who do they think they’re talking to? Framings of the audience by social media users. International Journal of Communication, 6, 1056–1076.
Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory. Chicago: Aldine Publishing.
Gruzd, A., Staves, K., Wilk, A. (2012) Connected scholars: Examining the role of social media in research practices of faculty using the UTAUT model. Computers in Human Behavior, 28 (6), 2340–2350
Litt, E. (2012). Knock, Knock. Who's There? The Imagined Audience. Journal of Broadcasting & Electronic Media, 56(3), 330-345,
Marwick, A. E & boyd.d. (2011). I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New media & society, 13(1), 114-133
Mewburn, I. & Thomson, P. (2013) Why do academics blog? An analysis of audiences, purposes and challenges. Studies in Higher Education, 38(8), 1105-1119.
Veletsianos, G. (2016). Networked Scholars: Social Media in Academia. New York, NY: Routledge.
Vitak, J. (2012). The impact of context collapse and privacy on social network site disclosures. Journal of Broadcasting & Electronic Media, 56(4), 451-470.
Background:
Twitter is one of the most popular social media platforms inside and outside academia. Researchers use Twitter to search for and disseminate research, communicate, network, and engage with a broader audience. In the academic context, Twitter is most notably used to improve one’s visibility (Haustein, Bowman, Holmberg, Peters & Larivière, 2014; Holmberg, Bowman, Haustein & Peters, 2014; Van Noorden, 2014). Twitter activity has been receiving increasing attention by academia as a potential indicator of research impact, alongside other social media-based metrics (altmetrics). Several studies suggest that Twitter might reflect public outreach and science communication activities, not measured by traditional bibliometric indicators (Haustein et al., 2014).
Objective:
To further investigate Twitter use in academia as an extension of scholars’ scientific network and as a diffusion channel, this paper looks at the Twitter activity of a specific community: information science schools and their faculty members. More specifically, we aim to answerthe following questions: 1) How much do information science schools and their faculty members use Twitter? 2) How are the members of this community connected on Twitter? 3) What do they tweet about?
Methods:
A list of the 30 North American iSchools was obtained from the website ischools.org. Using the schools’ website, we retrieved the list of all faculty members, and then searched for their Twitter account. We found a Twitter account for the 30 iSchools and 267 (33%) of the 803 faculty members. Using the Twitter API, we retrieve the date of creation, the number of tweets, the tweets content1 and the list of followers for each account found.
Results:
Preliminary results show a large disparity in the Twitter presence and activity of iSchools, with faculty members’ presence per institution ranging from 7% to 84% and activity ranging from 56 tweets/year to 19,067 tweets/year. Figure 1 shows the highly skewed distribution of tweets and followers where, in a Pareto-esque fashion, 20% of Twitter users send more than 80% of the tweets (left) and 20% have more than 80% of the total number of followers (right). 1 Only the last 3,200 tweets for each account are available from the Twitter API.
We applied the Blondel et al. (2008) community detection algorithm to the follower-followee network of scholars and institutions, and found eight distinct communities, mostly linked to institutional affiliation. Despite those clusters, the network is characterized by a high density of interconnections, which is not surprising given that following someone on Twitter does not require a high level of engagement. Furthermore, the most active and followed Twitter users are not central in this network, indicating that they are followed by people outside of the iSchools community. This suggests that the Twitter network is more than a simple extension of the professional network.
Looking at the 50 most frequently used hashtags by the iSchools community (Figure 2), based on the 132,638 tweets collected (24% of all tweets), one can see that library and information science related topics are among the most discussed. However, other frequently used hashtags relate to the general political and social context, showing that the iSchools community members also use Twitter to discuss topics that are not necessarily related to their work.
Conclusion:
The aim of this work was to assess the Twitter presence and activity of iSchools and their faculty members in order to determine whether it is used by scholars to expand their network and as a diffusion channel. Our results show that the Twitter network is not limited to professional connections and despite the fact that only a minority of faculty members (about 34%) have a Twitter account, these users reach a large number of people from outside the scientific community. This highlights Twitter’s potential as a tool for public outreach. In order to provide a more thorough description of the iSchools faculty members’ activity on Twitter, and to see how Twitter affordances (e.g., mentions, retweets, hashtags) are used, further studies could look at tweets content more systematically. Such studies could help understand to what extent this type of social media activity actually reflects scientists’ public outreach.
References:
Blondel, V.D., Guillaume, J.-L., Lambiotte, R., Lefebvre, E. (2008) Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment (10), P10008.
Haustein, S., Bowman, T.D., Holmberg, K., Peters, I., and Larivière, V. (2014). Astrophysicists on Twitter: An in-depth analysis of tweeting and scientific publication behavior. Aslib Journal of Information Management, 66(3), 279–296.
Holmberg, K., Bowman, T.D., Haustein, S., and Peters, I. (2014). Astrophysicists’ conversational connections on twitter. PloS ONE, 9(8), e106086–e106086.
Van Noorden, R. (2014). Online collaboration: Scientists and the social network. Nature, 512
Background:
Social media penetration has compelled higher education and organisations to consider the role of social media in various novel pedagogical learning settings (Linna et al, 2015; Pettersson et al 2014). We explored social media communication and perceptions of undergraduate engineers involved in an industrially focused annual worldwide competition to design and develop a racing car, where students are allocated project management and team leadership responsibilities (Gargiulo & Benassi, 2000; Gällstedt, 2003; Zika-Viktorsson, A., Sundström, P., & Engwall, M, 2006).
Objective:
The aim of the research was to understand the views of engineering students who are highly centralised in social media networks, and if they perceive the nature of their work differently than less central team members.
Methods:
During the project design phase, data from various sources were extracted from one academic institution. These data sources included meeting minutes, Computer Aided Design (CAD) files, project reports and Facebook communication in relation to the project’s Facebook page. This data extraction occurred between the 04-June-2013 and the 17-April-2015. Additionally, students periodically completed a questionnaire (consisting of 42 questions) about a range of project related factors. This WIP paper focuses on the analysis of the student Facebook communication in relation to the survey answers. Using the degree centrality figures for students from their Facebook network we compared these results to the survey answers using Spearmans rank correlation coefficient (small sample, unknown linear relationship, unknown number of outliers). There were 35 students who conversed via Facebook and of those a total of 23 students also completed the survey.
Results:
We found that from the 42 questions, three questions showed a significant correlation between centrality ranking and higher answers being given in a scale from 5 (very high) to 1 (very low). The first of these significant correlations concerned individual workload with the higher centralised individuals also perceiving that their workload was higher (Rho = 0.42264). There was also a significant positive correlation with highly centralised individuals and perception of group conflict (Rho = 0.51224) and group delays (Rho = 0.61839). These findings suggest that highly centralised students perceive that their workload is higher than that of their peers. They also appear to have a holistic view of the project, identifying conflicts and potential delays in the overall group as they bring different components of the engineering project together. It is also notable that the persons identified as having the highest centrality scores were the student project manager and team leaders.
Future Work:
The sample size in this study is small (23 individuals), but it is envisaged that the same analysis will be conducted with the 2015/16 cohort of design engineering students. This comparison between year groups will ascertain if the presented significant findings occur year-on-year rather than falsely significant. Furthermore, we wish to compare other available data sources such as the network of collaborations on project documents and CAD files, with the questionnaire results and Facebook communication to understand the digital footprint of the project manager and how, long term, we can digitally support them.
References:
Gargiulo, M., and Benassi, M. (2000) "Trapped in your own net? Network cohesion, structural holes, and the adaptation of social capital." Organization science 11.2: 183-196.
Gällstedt, M. (2003) "Working conditions in projects: perceptions of stress and motivation among project team members and project managers." International Journal of Project Management 21.6: 449-455.
Linna, P., Aramo-Immonen, A., Saari, M., Turunen, J., Jussila, J., Joel-Edgar, S., Huhtala, M. (2015) Assessment of Social Media Skills Among Vocational Teachers in Finland. EduLearn, Barcelona, Spain.
Pettersson, E., Aramo-Immonen, H., Jussila J.J. (2014) Social media utilization in b2b networks’ organisational learning – review and research agenda proposal. Journal of Mobile Multimedia, Vol. 10, No.3&4 (2014) 218 – 233
Zika-Viktorsson, A., Sundström, P., & Engwall, M. (2006) "Project overload: An exploratory study of work and management in multi-project settings." International Journal of Project Management 24.5: 385-394.
Background:
Metadata is a set of descriptive, technical and administrative information that plays a key role in image storage, processing and circulation. Recent literature in media studies highlights the roles metadata plays in domains such as digital economies and informational infrastructures. Many of these studies focus on the music sector: in particular, they tackle the automated or manual classification of songs, as well as the algorithmic systems of recommendation (Beer, 2013; Morris, 2012, 2015). In the field of visual culture, various publications emphasize the role that metadata plays in the classification of images by amateur and professional photographers (Van Dijck, 2010; Boullier and Crépel, 2013). But few broach the distinction between embedded metadata and platform-specific metadata. The former refers to data directly stored within the image file, which allows the data to travel with the picture on its journey across platforms, whereas the latter refers to data separately stored on proprietary web servers, including keywords, geotags and other folksonomies, which are lost when the picture is copied from one platform to another.
Objective:
This paper focuses on image metadata (in particular, photographic images) to illustrate how web platforms handle images, and how these technical choices are tied to different economic models of content and audience retention. Its aim is to challenge the assumption that the more an image circulates and is appropriated on social media, the more metadata it subsequently accumulates. This paper suggests instead that there is a critical distinction between the way embedded and platform-specific metadata accumulate.
Methods:
This study is based on a set of experiments conducted on a small corpus of photographs. In collaboration with a Canadian visual artist, five images of artworks were marked with embedded metadata and steganographic information before being posted on three different platforms (Wordpress, Facebook and Instagram). Six months later, all the copies in circulation were collected through Google Image reverse search and TinEye, and their metadata were extracted via an application named Exiftool. A quantitative and qualitative analysis was conducted on the metadata to compare 1) how the transit through each platform affected the embedded information and 2) what kind of platform-specific metadata was attached to these images. A complementary analysis was conducted on Flickr and Twitter with a random set of images.
Results:
The preliminary results suggest that contrary to platform-specific metadata that stably accumulate on web servers, embedded metadata is shaped by a complex dynamic of accumulation and degradation. On the one hand, social media platforms tend to strip embedded metadata out of their users’ images (this is especially the case with platforms designed for non-professional image-sharing practices, such as Facebook), while on the other hand, social media platforms encourage users to recreate this data in a proprietary format tied to the platform. Therefore, the more an image circulates beyond the thresholds of proprietary platforms, the more its metadata becomes degraded. The images that cross boundaries between platforms and travel through various social media datascapes are the most portable (see Sterne, 2006), but the quality of their metadata is poorer. In terms of audience retention, metadata stripping increases content captivity, as it makes it more difficult for users to move their archives from one platform to another, knowing that metadata (re)creation is a time- consuming operation.
Future Work:
This paper argues that paying thorough attention to the specificities of image metadata lays the groundwork for an understanding of the broader ecology of social media. Further work on larger datasets could foster insights regarding the power and economic dynamics of data streams within and across social media (Manovich, 2012; Hochman, 2014), all the while reflecting on the politics of web platforms (Gillespie, 2010; Helmond, 2015).
References:
Boullier D. and M. Crépel (2013). Biographie d’une photo numérique et pouvoir des tags : classer/circuler. Revue d’Anthropologie des Connaissances, 7(4), 785-813.
Gillespie, T. (2010). The politics of ‘platforms’. New Media & Society, 12(3), 347-364.
Helmond, A. (2015). The Platformization of the Web: Making Web Data Platform Ready. Social Media + Society 1(2).
Hochman, N. (2014). The social media image. Big Data & Society, 1(2). Available at: http://bds.sagepub.com/content/1/2/2053951714546645 (accessed 12 January 2016).
Manovich, L. (2012). Data stream, database, timeline: the forms of social media. Software Studies Initiative. Available at: http://lab.softwarestudies.com/2012/10/data-stream-database-timeline-new.html (accessed 12 January 2016)
Morris, J. W. (2012). Making music behave: Metadata and the digital music commodity. New Media & Society, 14(5), 850-866.
Morris, J. W. (2015). Selling Digital Music, Formatting Culture. Berkeley: University of California Press.
Sterne J. (2006.) The mp3 as cultural artifact. New Media & Society, 8(5), 825–842.
Van Dijck, J. (2010). Flickr and the Culture of Connectivity: Sharing Views, Experiences, Memories, Memory Studies, 4(4), 401-415.
Background
the proliferation of ‘self-tracking’ devices has become a recent focus of research into ‘everyday’ or ‘personal’ analytics, including historical antecedents (Crawford et al. 2015), implications for citizenship, health and biopolitics (Lupton 2014), self-tracking markets (Pantzar and Ruckenstein 2015), surveillance (Whitson 2013), and the broader ‘quantified self’ movement (Nafus and Sherman 2014). There has been relatively little qualitative analysis of the contexts in which such devices are ordinarily used, how the data is interpreted, used, and shared by individuals, and how such data relates to broader practices of temporal scheduling and coordination in daily life. This paper makes a significant contribution to knowledge, showing how such devices are becoming integrated with established technologies of marking and making time (clocks, calendars), are being used to explicitly manage time, and are ambiently shaping ‘lived time’ in diverse ways (Wajcman 2015).
Objective
The paper aims to provide detailed empirical data on how individuals do and do not adopt self-tracking devices and negotiate their own data in terms of the temporality of personal analytics. Drawing upon in-depth interviews, we show the different ways in which these devices presume, produce, mediate, manage and shape temporal practices.
Methods
The empirical data was gathered over several months as part of a larger SSHRC funded program concerned with the contours of ‘iTime’. The data used here is in-depth interviews (N=30) selected by quota sample to reflect the overall demographic of the university. There are two dimensions to this group being explored. First, multiple device ownership within this demographic is very high, but we know very little about their understanding and management of temporality through digital mediation, and how this relates to the specific expectations of university life, friendships and maintaining a connected presence’ across multiplying social media platforms. Second, approximately half of the sample (N=15) was selected for their ownership and use of wearable fitness applications (i.e. ‘fitbit’). This is a focused effort to understand emerging practices of self-tracking in relation to the production of temporal data about the self. We have rich data on the connections between these practices and the broader expectations within this group. Participants reflected upon their own devices and social media data during interviews.
Results
Preliminary analysis of our data reveals continuities between existing temporal practices, but also significant novel trajectories encouraging users to (a) rethink and reshape their conception and organization of time (b) share their data across social media platforms to regulate personal time, (c) meet new expectations about temporal management being produced through the tracked data.
Future Work
These findings will enable important insights into the normative temporal expectations of self-tracking devices, and how these are understood and negotiated both through social media and a range of integrative practices. How these devices become elements of people’s media ecologies or ‘manifolds’ is crucial to understanding their relative significance (Couldry 2012). These initial findings will also be revisited alongside interview data (N=100) from other populations being gathered during 2016, concerning differences in socio-economic resources, age, and urban proximity.
References
Couldry, N (2012). Media, Society, World. Cambridge: Polity.
Crawford, K., Lingel, J., and Karppi, T. (2015). Our metrics, ourselves: A hundred years of self-tracking from the weight scale to the wearable device. European Journal of Cultural Studies, 18 (4-5), 479-496.
Lupton, D. (2014). Quantified Sex: A Critical Analysis of Sexual and Reproductive Self- Tracking Apps. Culture, Health and Sexuality, 17(4), 440–53.
Nafus, D., Sherman, J. (2014). This one does not go up to 11: the Quantified Self movement as an alternative big data practice. International Journal of Communication, 8 (11), 1784-1794.
Pantzar, M., Ruckenstein, M. (2015). The heart of everyday analytics: emotional, material and practical extensions in self-tracking market. Consumption Markets & Culture, 18(1), 92–109.
Ruckenstein, M. (2014). Visualized and Interacted Life: personal analytics and engagements with data doubles. Societies, 4, 68-84.
Wajcman, J. (2015) Pressed for Time. Chicago: Chicago University Press.
Whitson, J. (2013). Gaming the Quantified Self. Surveillance and Society, 11 (1/2), 163-167.
Background:
The rate of sexual assaults in dense metropolitan spaces in Canadian cities (with 100,000 inhabitants or more) has not declined since as far back as 1999 (Perreault, 2015). This continues to be a particular concern in and around public transportation systems, such as buses, trains, and metros (Gekoski et al., 2015). In the quest to integrate technology as an innovative approach to end sexual violence against girls and women, a number of mobile phone apps (Circle of 6), crowd-sourcing websites (Hollaback!), and geo-mapping platforms (HarassMap) have been developed to help girls and women call on close friends and family as support before or after impending sexual assaults occurred. But what about influencing strangers standing in public spaces, where there is an immediate opportunity to intervene, to interrupt violence perpetrated against girls and women before it happens?
Objective and Methods:
A three-month doctoral candidacy exam review was conducted on the title question, with a number of sub-questions explored: 1 – What theories exist informing research on nonviolent prosocial helping behaviours? 2 – What technologies (mobile phones & LCD screens) are currently being used to address sexual violence? 3 – What methods exist to evaluate the efficacy and effectiveness of these technologies? A second month-long review adds an examination on social work theory, practice, and policy, and on the intersectionalities between gender, identity, and the realities of victimization affecting women as well as men.
Results:
Theories explaining the Bystander Effect (Latané & Darley, 1970) and the Diffusion of Responsibility (Darley & Latané, 1968) show that people do intervene, particularly when situations are recognized as an emergency, prove to be dangerous, and fewer people are present (Fischer et al, 2011). Empathy training is not entirely effective (Schewe & O’Donohue, 1993). Persuasive technology researchers would be wise to focus less on influencing prosocial attitudes and favor showing helping behaviours exhibited in similar situations (Fabiano et al. 2003). Recognizing the value of digital technologies to support social work policy and practice is controversial (Sapey, 1997) but is growing (Goldkind & Wolf, 2015).
Future Work:
Mass Interpersonal Persuasion (Fogg, 2008) models offer innovative solutions for designing persuasive messages in and around public transport spaces. Including pre-and post effectiveness evaluations (Gekoski et al., 2015) and men’s voices in future program and policy evolutions (Birchall, Edstrom, & Shahrokh, 2016) is the next step in this important work in improving on the efficacy (Glasgow, 2003) of bystander intervention surveys (Banyard, 2008). Future doctoral work will explore the use of visual arts-based research methodologies for social change, policy development (De Lange, Mitchell, & Moletsane, 2015), and creating networks of supportive relationships (Bock, 2012) at the local as well as international level.
References:
Banyard, V. L. (2008). Measurement and correlates of prosocial bystander behavior: The case of interpersonal violence. Violence and Victims, 23(1), 83–97.
Birchall, J., Edstrom, J., & Shahrokh, T. (2016). Reframing men and boys in policy for gender equality. Retrieved from ~opendocs.ids.ac.uk/ 123456789/9709/FINAL%20DESIGNED%20VERSION.pdf
Bock J. G. (2012). The technology of nonviolence: Social media and violence prevention. Cambridge, MA: MIT Press.
Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility. Journal of Personality and Social Psychology, 8, 377–383.
De Lange, N., Mitchell, C., & Moletsane, R. (2015). Girl-led strategies to address campus safety: Creating action briefs for dialogue with policy makers. Agenda, 29(3), 118–127.
Fabiano, P. M., Perkins, H. W., Berkowitz, A., Linkenbach, J., & Stark, C. (2003). Engaging men as social justice allies in ending violence against women: Evidence for a social norms approach. Journal of American College Health, 52(3), 105–112.
Fischer, P., Krueger, J. I., Greitemeyer, T., Vogrincic, C., Kastenmüller, A., Frey, D., ... & Kainbacher, M. (2011). The bystander-effect: a meta-analytic review on bystander intervention in dangerous and non-dangerous emergencies. Psychological Bulletin, 137(4), 517–537.
Fogg, B. J. (2008). Mass interpersonal persuasion: An early view of a new phenomenon. In Persuasive Technology (pp. 23–34). Springer Berlin Heidelberg.
Gekoski, A., Gray, J. M., Horvath, M. A. H., Edwards, S., Emirali, A. & Adler, J. R. (2015). ‘What Works’ in Reducing Sexual Harassment and Sexual Offences on Public Transport Nationally and Internationally: A Rapid Evidence Assessment. London, UK.
Glasgow, R. E., Lichtenstein, E., & Marcus, A. C. (2003). Why don't we see more translation of health promotion research to practice? Rethinking the efficacy-to-effectiveness transition. American Journal of Public Health, 93(8), 1261–1267.
Goldkind, L., & Wolf, L. (2015). A digital environment approach: Four technologies that will disrupt social work practice. Social Work, 60(1), 85–87.
Latané, B., & Darley, J. M. (1970). The unresponsive bystander: Why doesn’t he help? New York, NY: Appleton-Century-Croft.
Perreault, S. (2015). Criminal victimization in Canada, 2014. Canadian Centre for Justice Statistics, Catalogue no. 85-002-X ISSN 1209–6393. Retrieved from statcan.gc.ca/pub/85-002-x/2015001/article/14241-eng.pdf
Sapey, B. (1997). Social work tomorrow: Towards a critical understanding of technology in social work. British Journal of Social Work, 27(6), 803–814.
Schewe, P., & O’Donohue, W. (1993). Rape prevention: Methodological problems and new directions. Clinical Psychology Review, 13, 667–682.
Background:
Social media offers qualitative researchers volume, richness and the promise of direct access to the lived experience of the individual. However, the scale and complexity of social media data presents a “little big data” challenge in terms of data collection, aggregation and interpretation (Esomar 2014). Social media identity production is located within an online infrastructure that reproduces a world “out there” (Pridmore & Lyon 2011) and involves the curation of numerous data fragments within ongoing episodic narration. Established qualitative data collection and analysis can struggle to capture fully this longitudinal and iterative process. We contend that new methods of qualitative data collection and analysis are needed to capture the longitudinal adjustment to social norms; self-censorship and the translation of the self into content in order to provide a holistic understanding of the online identity production.
Objective:
Our paper synthesises filmic methods and consumer research theory to develop an innovative methodology, which captures the interactive process-based nature of social media identity production.
Methods:
We implement a four-phase mixed-methods methodology, which forms a prism of reflexive data collection and analysis. We recruited professional filmmakers to construct films composed of a discrete chosen participant’s social media data. In the first phase, the professional filmmakers acted as expert interpreters and constructors of narrative. These filmmakers constructed a biopic of selected research subjects using longitudinal data (words, pictures, speech and music) extracted from social media platforms. The filmmakers were not informed of the research agenda and focussed solely upon the subject’s online identity as enacted on social media. The filmic process involved the synthesis and aggregation of data into a themed narrative. Second, the subject responded to the filmic representation of their online identity. Third, the filmmaker responded to the subject response. Fourth, the final films and accounts by participants and film makers were analysed.
Results:
We report on our experience of using this method and argue that this approach enhances understanding of the disclosed and the (re)-interpreted self within social media. Our work shows that social media identity production involves reconciliation with the temporal self, harmonizing multiple selves and reconciling the dichotomous public/private self. The resultant findings advance understanding of celebritisation and marketisation of the self in contexts where public and private merge in increasingly challenging ways.
Future Work:
We plan to synthesise film production and interpretive consumer research theory to propose a robust methodological framework for the presentation and analysis of social media activity. Our work will provide a nuanced and reflexive template for research into digital narrative construction and self presentation.
References:
Esomar (2014) Big Data and the Future of Qualitative Research, RW Connect, Retrieved from http://rwconnect.esomar.org/big-data-and-the-future-of-qualitative-research/, Accessed 2016-01-15
Pridmore, J., & Lyon, D. (2011). Marketing as Surveillance: Assembling Consumers as Brands, In D. Zwick & J. Cayla, (Eds), Inside Marketing (pp. 115-136). Oxford: Oxford University Press.
Background:
The growing use of social media has brought both opportunities and challenges to organizations. One of these challenges is the uncontrolled spread of content on social media that could potentially damage the reputation of the organization and its members (e.g. Meijer & Kleinnijenhuis, 2006). Social identity theory can be used to explain how organizations and their members cope with such phenomena (e.g. Petriglieri, 2011). Some organizations attempt to counter negative outcomes by imposing social media standards on their members, as one of the many ways in which the organization tries to enforce their employees’ loyalty. Employees, however, are then confronted with various characteristics of what Coser (1974) and Peterson and Uhnoo (2012) refer to as a ‘greedy institution’.
Objective:
In this paper, we explain how police officers – who strongly identify with their organization and profession – cope with both threats to their organizational and professional identity emerging from external pressure (e.g. social media content) as well as demands of total commitment from their organization.
Methods:
For this study, a mixed method approach is used. Data analysis is based on 32 semi-structured interviews and focused probes (following a Q-sorting experiment) in a large police region in The Netherlands. The interviews (which lasted from 35 minutes to one and a half hour) were executed by two researchers, tape-recorded and transcribed verbatim.
Results:
In line with social identity theory (Tajfel & Turner, 1979), police officers try to maintain a positive social identity. As their identity is threatened by, for example, social media content, they engage in identity management strategies.
Contrary to what was expected based on social identity theory, police officers – who strongly identify with their organization, and even stronger with their profession – do not frequently choose an identity management strategy that actively protects their social identity in case of an identity threat. Instead of positively distinguishing their threatened identity, they, for example, conceal their police identity in private times or condemn the condemners (Petriglieri, 2011). This can be explained by the finding that the Dutch Police shows striking similarities with Coser’s (1974) description of a greedy (highly demanding) institution. The police organization wants to ensure that police employees actively protect the organizational image in case of a threat and refrain from possible image threatening behavior. In order to avoid negative organizational image and subsequent legitimacy losses, appropriate behavior is enforced by the organization under the pretext of:
“Don’t forget… everything you do is under a magnifying glass. You, literally, live in a glass house. For the smallest mistake you might make, you could be reprimanded or even fired.” (R8)
Our focused interviews reveal that tensions arise when police employees at the same time try to protect their professional identity and their ‘personal space’ when their professional identity is threatened in private times. Police employees, then, perceive a threat not merely as an identity threat, but also as a threat to their work-private boundary. The struggle police employees experience because they, on the one hand, want to speak up to protect their threatened and so much ‘beloved’ professional identity, and on the other hand want to enjoy their off-time, is well reflected in the following quote:
“You are proud of your work (…). So, every now and then, I do get tossed back and forth, because on the one hand, you don’t like that people always talk negative about your work, but on the other hand, you don’t always feel like ending up in discussions. (…) In first instance, I would try to keep my mouth shut, but eventually, um, if I do fall for the provocation, I would defend it.“ (R21)
In accordance, police officers not merely use identity management strategies to protect their threatened identity. They also use these strategies as boundary mechanisms: to enhance vigilance against total intrusions of their personal identity.
Future Work:
Data analysis is already at an advanced stage. A first draft of a paper will be presented at the conference. Feedback will be welcomed. The paper is one of the studies in the PhD project of the first author.
References:
Coser, L. A. (1974). Greedy institutions: Patterns of Undivided Commitment. New York: Free press.
Meijer, M. M. & Kleinnijenhuis, J. (2006). News and corporate reputation: Empirical findings
from the Netherlands. Public Relations Review, 32, 341-348.
Peterson, A. & Uhnoo, S. (2012). Trials of loyalty: Ethnic minority police officers as ‘outsiders’
within a greedy institution. European Journal of Criminology, 9 (4), 354-369.
Petriglieri, J. L. (2011). Under threat: responses to and the consequences of threats to
individual identities. Academy of Management Review, 36 (4), 641-662.
Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In W. G. Austin,
& S. Worchel (Eds.), The social psychology of intergroup relations (pp. 33-47).
Monterey, CA: Brooks Cole.
Background:
The U&G approach has a longstanding history in communication research and, most recently, social media research (Quan-Haase & Young, 2010). Past research showed that Twitter users gain a wide range of gratifications, of which the most important was a need for social connection (Chen, 2011). Johnson and Yang (2009) corroborate and expand these findings by showing that what motivates users is a need to maintain contact with friends and family, to communicate with many people simultaneously, and to pass the time. Smock et al. (2011), on the other hand, took a more targeted approach and investigated the U&G of Facebook features. The present study builds on this past research.
Objective:
While most prior research has examined the gratifications gained from the Twitter platform as a whole, we were interested in the gratifications associated with specific features. What motivations predict the use of specific Twitter features? Why do users choose to retweet or employ a hashtag? Does one feature provide different benefits from other features? Obtaining insights into what motivates users to employ specific features has three important insights. First, it will help developers as they update the site. Second, it will inform how microblogging works in the context of user needs. Finally, it will provide a more fine-tuned understanding for why users prefer one social media tool to another. Past work by Quan-Haase and Young (2010) has called for a need for more comparative research. We need to understand how social media platforms work in relation to one another, as a majority of users adopt more than one platform (Duggan et al., 2015).
Methods:
A paper- and web-based survey was used to collect data relating to social media use. Participants were predominantly women (74%) with an average age of 28. Of the initial pool of 222 participants, 162 indicated they use Twitter and 142 of these completed the survey. Twitter users were asked about their frequency of use of features (e.g., tweet, retweet), based on previous work by Coursaris et al. (2013). Factor analysis was used to help develop U&G variables that could be included in six multivariate analyses with six Twitter features as the dependent variables and the U&G variables as the independent variables.
Results:
More than half of the participants (56%) reported using Twitter for four years or more, though they tended to use Twitter less than one hour per day (59%). The majority of the participants used the following features at least weekly: timeline, tweet, retweet, #, @, and search. Not unlike the Facebook (Smock et al. (2013), features were correlated (.49 to .78), but were not measuring the same things. Four U&G factors were extracted using principal components analysis: (1) Professional, (2) Leisure, (3) Social, and (4) Escape. Several U&G items were removed during analysis due to cross- or low-loading. Some of Coursaris et al.’s (2013) original factors converged, but were retained as the composites made sense at face value (e.g., information and professional advancement).
All six multiple regression analyses were significant (p < .001). All six twitter features share a significant relationship to the Professional U&G of Twitter. In contrast, Escape was not significantly related to any features. The Leisure U&G shared a significant relationship with participants’ timeline viewing (p < 0.001) and use of the search function (p < .5). Social U&G were significantly related to timeline (p < .05), tweet (p < .01), and @ (p < .01).
Future Work:
The results indicate that specific features are related to different U&G constructs and suggest the potential of operationalizing U&G factors through Twitter feature use. Further, big data analysis has the potential to expand on this work by showing what features users are making use of in what contexts. This work establishes a baseline for future work that will allow to compare various social media platforms and show how they provide different U&G for users in different social contexts.
References:
Chen, G. M. (2011). Tweet this: A uses and gratifications perspective on how active Twitter use gratifies a need to connect with others. Computers in Human Behavior, 27(2), 755–762.
Coursaris, C. K., Sung, J., Osch, W. Van, & Yun, Y. (2013). Disentangling Twitter’s adoption and use (dis)continuance: A theoretical and empirical amalgamation of uses and gratifications and diffusion of innovations. Transactions on Human-Computer Interaction, 5(1), 57–83.
Duggan, M., et al. (2015). Social media update 2014: While Facebook remains the most popular site, other platforms see higher rates of growth. Retrieved from http://www.pewinternet.org/2015/01/09/social-media-update-2014/
Johnson, P. R., & Yang, S.U. (2009). U&G of Twitter: An examination of user motives and satisfaction of Twitter use. Paper presented at the Communication Technology Division of the annual convention of the Association for Education in Journalism and Mass Communication, Boston, Massachusetts.
Quan-Haase, A., & Young, A. L. (2010). Uses and gratifications of social media: A comparison of Facebook and instant messaging. Bulletin of Science, Technology and Society, 30(5), 350–361. Retrieved from http://bst.sagepub.com/content/30/5/350.abstract
Smock, A. D., Ellison, N. B., Lampe, C., & Wohn, D. Y. (2011). Facebook as a toolkit: A uses and gratification approach to unbundling feature use. Computers in Human Behavior, 27(6), 2322–2329. doi:10.1016/j.chb.2011.07.011
Background:
There are also trends in social media research to explore the process and mechanism of social media impact, for instance, whether the effect depends on individuals’ intrinsic properties or particular features of their environment. Previous studies generally considered individual characteristics such as personalities as independent predictors of social media behaviour as well as its outcomes, but paid little attention to the potential bridging role of a user’s personality in the process of effects occurring.
An earlier study (Swickert, Hittner, Harris, & Herring, 2002) considered the moderating role of personality in the association between Internet use and social support, and found marginally significant interaction effects. A recent research (Kim, Hsu, & Zuniga, 2013) found that impact of social media on civic participation and discussion heterogeneity was moderated by individuals’ extraversion and openness to experience. To investigate the role of personalities in the association between social media use and perceived social capital, this study applied the Five-Factor Model (FFM), which is also known as the Big Five. The FFM divides personality into five dimensions, including extraversion, openness, neuroticism, conscientiousness, and agreeableness, which have greatly helped previous research involving the investigation of individual differences (Barrick & Mount, 1991).
Objective:
Given the above, the present study took steps to explore the moderation effects of personality traits (i.e., extraversion, openness, neuroticism, conscientiousness, and agreeableness) in the relationship between social media use and interpersonal relationships.
Methods:
An online survey was carried out by the research faculty of media and communication located at the Hokkaido University. Questionnaire was designed based on previous studies and posted on the web-survey platform of a research institute. An invitation email with the URL link to the electronic version of the questionnaire was sent to Chinese Weibo users of the panel of the research institute. Within one week, a total of 821 valid samples (male=400, female=421) with a response rate of 28.4% were collected for analyses in the present study.
Results:
Results of hierarchical regression suggested that personality traits, including extraversion, openness, neuroticism, and agreeableness, have potential power to determine the degree of relational benefits gained from social media use.
Future Work:
Besides the findings and implications, several limitations should be addressed. One of them is related to the measurement of social capital used in this study. Items are mostly self-reported judgments rather than real estimation of social capital. Therefore, future research may consider measuring social capital in more practical contexts. For instance, taking individuals’ civic participation, interpersonal trust, and social network size as dimensions to represent their actual social capital. Second, this study tested the moderation effects by using hierarchical multiple regression. However, linear regression has limitations in variable control. To achieve more rigorous explanation of the interacting effects, future research is suggested to use more sophisticated methodologies that can better rule out the intervention of irrelevant variables, for instance, using the structural equation modeling.
References:
Kim, Yonghwan, Hsu, Shih-Hsien, & Zuniga, Homero Gill de. (2013). Influence of social media use on discussion network heterogeneity and civic engagement: The moderating role of personality traits. Journal of Communication, 63, 498-516.
Barrick, Murray R, & Mount, Michael K. (1991). The big five personality dimensions and job performance: A meta‐analysis. Personnel psychology, 44(1), 1-26.
Swickert, Rhonda J, Hittner, James B, Harris, Jamie L, & Herring, Jennifer A. (2002). Relationships among Internet use, personality, and social support. Computers in Human Behavior, 18(4), 437-451.
The speech will focus on the results of the Tempus European Project eMEDia dedicated to Cross-Media Journalism. The project is founded by the European Commission as it involves four European partners - IULM University, Tampere University, University of Barcelona, and the Mediterranean network Unimed - and three Tunisian Universities – IPSI La Manouba, Sfax and Sousse – along with the Tunisian Ministry for Higher Education and the National Syndicate of Journalists. The focus on Tunisian condition is basically due to the role played by digital activists in its recent history.
The research is dedicated to the relationship between political participation, news-making practices and the spread of social media, as it is affecting Tunisian society. As we know, Tunisia during the Arab Spring had been widely considered as a laboratory for the analysis the use of new technologies for political participation. Nonetheless, the literature about the Arab Spring actually fell short in explaining the genesis of the phenomenon, on the one hand by isolating technologies as a casual factor in the spread of demonstrations, and on the other by analyzing North-African condition through a biased perspective. Nowadays, it is interesting to focus on the consolidation of the information environment three years after the uprisings. And what is relevant, only a close, in- depth analysis of Tunisian society is able to provide an explanation of its history, and namely of the part of digital media in the overall evolution of political system. That is why the research is based on different methodologies: desk stage, interviews, and in-depth analysis of communication practices.
Networked journalism is the condition determined by the technological innovation on news-making activities: a condition upon which professional journalist can no longer be considered the only player in the information arena, and a new skill must be developed. Along with democratization, nonetheless, the so-called citizen journalism is also likely to produce some ambiguous effects, such as the lack of professional standards and the spread of information cascades, which may prove to be particularly dangerous in an evolving media market as the Tunisian one. This is why, according to the project, a new profile must be defined, which is able to manage this new condition, and which can be hardly reduced to the parameters of traditional journalistic work. Rather than simply using new devices for news visualization, communication professionals must also be able to dialogue with all new players and to accept the decentralized nature of digital environments. This networked nature of news- making seemed to emerge during the Tunisian revolution, when bloggers, journalists and activists used to retweet each other. Nonetheless, this intensification of communication exchange was inspired by the political climax of the uprising, while all media, by definition, are also supposed to bring some effects on people’s state of mind, culture and daily life routines. That is why it is worth analyzing the consolidation of these practices in a normal, post- revolutionary situation.
This study examines how new media has facilitated sweeping changes across the entire spectrum of propaganda, ranging from production and dissemination to reception. Drawing on Actor Network Theory, an alternative view to traditional conceptualizations of the processes involved in the making of propaganda is presented. The applicability to Internet of the traditional unidirectional model of propaganda as Sender, Message and Receiver is questioned, and juxtaposed to the nondeterministic perspective that an Actor Network model offers. The online propaganda and counterpropaganda campaigns currently being waged by the Islamic State in Iraq and Syria (ISIS) and the US State Department are presented and contrasted as examples of the old and new models of propaganda.
Methods:Drawing on works from Science and Technology Studies, especially the works of Bruno Latour (1987, 1991, 2005), the study takes into account factors such as, decentralization of sources, democratization of actors, flexibility of the network with its focus on the entire propaganda making process. In contrast to the functionalist understanding, which considers the Internet as a ‘tool’ used by human beings in disseminating the messages, it regards the Internet as an actual ‘actor’ in the design and shaping of propaganda. That is to say, it is Internet that is the main actor in transforming the nature of terrorist propaganda.
Results:This work-in-progress paper suggests that Internet has not only vastly increased the ease of access and extent of dissemination but more importantly, due to the inclusion of myriad actors, it has radically transformed the way propaganda is being made. Through an analysis of the social media campaigns being waged by the Islamic State in Iraq and Syria (ISIS) and the US State Department, we argue that the Internet has brought about a shift in the field of propaganda.
References:
Cohen, Almagor R. (2012). In Internet’s way: Radical, terrorist Islamists on the free highway. International Journal of Cyber Warfare and Terrorism, 2(3), 39-58.
Conway, M. (2006). Terrorist use of the Internet and fighting back. An International Journal, 19, 9-30.
Denning, D E. (2010). Terror’s web: How the Internet is transforming terrorism. In: Jewkes Y and Yar M (eds). Handbook of Internet Crime. Devon: Willan Publishing, pp: 194-213.
Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Harvard University Press: Harvard.
Latour, B. (1991) Society is technology made durable: In Law J (ed). A sociology of monsters: Essays on power, technology and domination. Routledge: London.
Latour, B. (2005). Reassembling the social: An introduction to Actor-Network Theory. New York: Oxford University Press.
Weimann, G. (2004). www.terror.net. How modern terrorism uses the Internet. United States Institute of Peace Report, March.
Weimann, G. (2006) Virtual disputes: The use of the Internet for terrorist debates. Studies in Conflict & Terrorism, 29 (7): 623-639.
Background:
This paper is based on a chapter entitled “Coding of non-text data” (Rasmussen Pennington, in press) that has been accepted for publication in The SAGE handbook of social media research methods. The chapter outlines the special concerns associated with collecting and analyzing data found on social media sites and not in language-based text (Rasmussen Neal, 2012). The presence of non-text information on social media sites, such as photographs, videos, music, and even games on Facebook, Twitter, Instagram, Flickr, Pinterest, Snapchat, YouTube, and Vine, continues to grow exponentially. Despite their abundant presence, and the wealth of insight that social media researchers could obtain from them, few methods have been developed and utilized to use them. They are naturalistic, “found” data sources, just as tweets and blog posts are, but they are frequently ignored in favour of text-based data.
Objective:
The objectives of this paper are: (1) to outline qualitative research methods that can be used to analyze non-text social media data and illustrate them with examples, and (2) to set forth an agenda for developing this underdeveloped area of research methods.
Methods:
The methods to be overviewed will include compositional interpretation, quantitative content analysis, qualitative content analysis, and approaches related to content analysis such as document analysis and musical analysis. Next, methods influenced by cultural understandings will be reviewed, including approaches from the disciplines of cultural studies, visual sociology, visual anthropology, semiotic analysis, and iconography/iconology. Finally, analyses influenced by social understandings, including discourse analysis, visual social semiotics, and multimodal research, will be discussed. Since many methods will be outlined in a short amount of time, a list of resources for reading about the methods will be provided at the session.
Results:
The purpose of this paper will not present original empirical results; instead, it is meant to introduce social media researchers to potentially new data sources as well as methods for analysing them. Results from the author’s previous studies in this area will be used as examples.
Future Work:
The second part of this paper will be to discuss what the methodological future of this emerging area of research might look like, with an eye toward engaging the audience in contemplation and discussion about the unique questions surrounding non-text research. As discussed in the chapter, questions about the development and implementation of non-text methods include:
References:
Rasmussen Neal, D. (Ed.) (2012). Indexing and retrieval of non-text information. Berlin: De Gruyter Saur.
Rasmussen Pennington, D. (in press). Coding of non-text data. In A. Quan-Haase and L.
Sloan (Eds.), The SAGE handbook of social media research methods. Thousand Oaks, CA: SAGE Publications.
Background:
On the 28th of June 2015, thousands of people gathered in a large pedestrian area of Istanbul to peacefully celebrate Istanbul Pride, an annual gay and LGBT event. Shortly after assembling, the event was suddenly disrupted by the city’s police who assailed participants with rubber pellets, tear gas, and water cannons. As typical of Turkey, a country with limited press freedoms (see Furman 2015), there was no coverage in the mass media of what occurred during the event. Nonetheless a few hours after the event, Instagram was flooded with pictures of the violence that had ensued.
Objective:
While a growing body of work theorizes the role of Twitter and Facebook in social change (Gerbaudo 2012; Leavitt 2009; Poell et al. 2015; Procter et. al 2013), little has been done to explore how Instagram is used during political events such as demonstrations. This paper engages the question of whether Instagram’s affordances designate it to be a medium archiving and structuring the mundane exclusively or a tool for political mediations. We explore how users conceptualize the affordances of the platform and the agency they have in using it for their own motives. At stake is the question of whether users of this imagedriven mediumwho are at least to some degree invested in the politics of visibility that underlies the Pride Paradeare able to forge a disruption of, or intervention into, the mundane as it is cultivated on social media. In Turkey, this might not only mean subverting the forms of control that the platform exercises over the streams of everyday communication but also challenging censorship and mood manipulation by progovernment forces.
Methodology:
Instagram is a mobile photosharing application and social network that offers it’s users a way to upload photos, apply different manipulation tools (f ilters) to transform visual elements of an image and share these photos (see Hochman & Schwartz 2012; Hochman & Manovich 2013). One way to share is to relate images with one another through hashtags. When a hashtag is used, the uploaded image is included with all other photos sharing the same hashtag. The act of tagging makes the image accessible not just to an inner circle, but to the wider Instagram public. Accordingly, one may argue that there is intentionality implicit in the act of tagging: by opting to use this feature, the user is making a connection between the uploaded image and the public image repositories.
A snowballing methodology was used to compile a list of hashtags related to 2015 Istanbul Pride. Then, using the Digital Methods Initiative’s Instagram scraper (Borra 2015) over 30,000 posts were collected in the days immediately after the event. Afterwards, the relationships between hashtags in the dataset were visualized with Gephi.
Results:
Gephi’s modularity algorithm detected two cohashtag communities in the dataset. Our visualization suggests that the affordances of Instagram were used in a strategic manner by participants to insert images of violence into seemingly unconcerned feeds. A phenomenon that be tentatively described as "stream hacking" occurred.
Future Work:
As a work in progress, our paper intends to explore the qualitative dimensions of “stream hacking” on Instagram through a series of semistructured, indepth interviews with users who participated in the action. Questions will address conceptions of platform affordances as well as any possible motivations.
References:
Borra, E. (2015). Instagram Scrapper. English, Amsterdam: Digital Methods Initiative. Retrieved from https://tools.digitalmethods.net/beta/instagram/
Cardullo, P. (2015). “Hacking multitude” and Big Data: Some insights from the Turkish “digital coup.” Big Data & Society, 2(1). http://doi.org/10.1177/2053951715580599
Furman, I. (2015). Alternatif Medya olarak Akranlararası Kolektif Üretim: 2013 Gezi Parkı Eylemleri’nde Ekşisözlük’ün rölüne dair bir inceleme. In B. Çoban & B. Ataman (Eds.), Türkiye’de Alternatif Medya : Direniş Çağında (pp. 199–223). Istanbul: Epsilon.
Gerbaudo, P. (2012). Tweets and the streets: social media and contemporary activism. London: Pluto Press.
Hochman, N., & Manovich, L. (2013). Zooming into an Instagram City: Reading the local through social media. First Monday, 18(7). http://doi.org/10.5210/fm.v18i7.4711
Hochman, N., & Schwartz, R. (2012). Visualizing Instagram: Tracing Cultural Visual Rhythms. In Proceedings of the Workshop on Social Media Visualization (SocMedVis) (pp. 6–9).
Hoyng, R. (2015). From Infrastructural Breakdown to Data Vandalism: Repoliticizing the Smart City? In Television and New Media.
Leavitt, A. (2009). The Iranian Election on Twitter: the first 18 Days. New York: Web Ecology Project. Retrieved from http://www.webecologyproject.org/wpcontent/uploads/2009/08/WEPtwitterFINAL.pdf
Poell, T., Abdulla, R., Rieder, B., Woltering, R., & Zack, L. (2015). Protest leadership in the age of social media. Information, Communication & Society, 1–21. http://doi.org/10.1080/1369118X.2015.1088049
Procter, R., Vis, F., & Voss, A. (2013). Reading the riots on Twitter: methodological innovation for the analysis of big data. International Journal of Social Research Methodology, 16(3), 197–214. http://doi.org/10.1080/13645579.2013.774172
Background:
In day to day life, people signal their membership in social groups in many different ways. Whether consciously or unconsciously, individuals shape and communicate their social identities through their interactions with others (Mead, 1934). While face to face interactions feature an abundance of identity cues, including speech, clothing, and gesture, in online environments, where text dominates, many of these cues are absent. Furthermore, there is an element of anonymity, or at least pseudonymity, built into most information and communications technologies (ICT) that exacerbates identity issues (Donath, 2007).
In this paper, we argue that self-references and inside jokes in the form of internet memes – “discursive artifacts spread by mediated cultural participants” (Milner, 2013) – are used by some online communities to signal and enhance group identity. These memes can function as a sort of online secret handshake, marking those who respond appropriately as “members of a subculture [who] share a common language” (Hebdige, 1979, p.122). In addition, by sharing, mixing, and remixing memes, participants engage in a form of mediated ritual communication, whereby group identity is co-created and maintained (Miller, 2015). As the subject of research, memes may also be able to provide insight into the character of an online community. Are the most popular memes positive or negative? Do the memes reference particular domains of media or culture? How has the memetic signature of the community changed over time?
In this exploratory study, we examine the character of the Reddit community, as revealed through its use of internet memes. Reddit was initially conceived as a social news-sharing site, but has grown into “one of the most populated spaces for digital sociality on the web today” (Miller, 2015, p.2) and has proved to be fertile ground for research (Bogers & Wernersen, 2014; Tan & Lee, 2015; Singer, et al, 2014). In analyzing the “Redditor” identity memetically, we aim to develop a new approach to the study of online communities.
Objective:
This work-in-progress seeks to compile a “memetic canon” of the Reddit community by documenting its most notable memes. Specifically, we intend to gather data on which memes Reddit users (“Redditors”) consider to be most important in defining themselves as a community and how the popularity of these memes change over time.
Methods:
Reddit, as a community, loves to talk about itself. Discussion threads where Redditors analyze the site and each other are commonplace, as are threads aimed at explaining jokes to new users or collecting “best-of” postings. From these meta-Reddit threads, we can identify notable memes within the Reddit community. Once identified, we can track past and future references to these memes in comments posted, describe trends, and analyze Redditor responses.
Results:
Forthcoming.
Future Work:
As a follow up to this study, we intend to conduct surveys and interviews of the Reddit users to determine how closely the image actual Redditors have of themselves matches our derived portrait. In addition, we would like to investigate sub-groups within the “Redditor” group identity and community interactions between subreddits.
References:
Bogers, T. & Wernersen, R. (2014). How ‘social' are social news sites? Exploring the motivations for using Reddit.com. iConference 2014 Proceedings, 329 – 344.
Donath, J. (2007). Signals in social supernets. Journal of Computer‐Mediated Communication, 13(1), 231-251.
Hebdife, D. (1979). Subculture: The meaning of style. New York: Methuen.
Mead, G. H. (1934). Mind, self, and society. Chicago: University of Chicago, 173-175.
Miller, C. (2015). Life in the new media landscape. gnovis, 16(2), 1-15.
Milner, R. M. (2013). Media lingua franca: Fixity, novelty, and vernacular creativity in internet memes. Selected Papers of Internet Research, 14, 1-5.
Singer, P., Flöck, F., Meinhart, C., Zeitfogel, E., & Strohmaier, M. (2014, April). Evolution of Reddit: From the front page of the internet to a self-referential community? Proceedings of the companion publication of the 23rd international conference on World wide web companion, 517-522.
Tan, C., & Lee, L. (2015, May). All who wander: On the prevalence and characteristics of multi-community engagement. Proceedings of the 24th International Conference on World Wide Web, 1056-1066.
Background:
With the advent of the Web, the way bank customers perform various banking activities has changed over the years which has brought about the concept of social media banking. This refers to the use of social media as a form of delivery channel for banking services which may include balance inquiries, account opening and fund transfers. Banking using social media channels is relatively new and any idea that is perceived as new should be considered an innovation worthy enough to be studied.
Objective:
The objective of the study is to investigate and compare social media banking acceptance and adoption across two countries namely Nigeria and England and to identify what factors have significant effects on consumer attitudes and behavioural intentions towards social media banking.
Methods:
The study will use the Unified Theory of Acceptance and Use of Technology (UTAUT) model developed by Venkatesh et al (2003). This model has been selected because it incorporates a range of variables from several models that have been used to understand technology acceptance and adoption. Venkatesh et al compared and summarized eight existing models of user acceptance theories and based on their results, they refined the eight models and merged it into an integrated single model which captures elements of the different models.
The UTAUT model was developed from theories in sociology and psychology and these theories are namely the Theory of Reasoned Action (TRA) (Ajzen and Fishbein, 1980), the Technology Acceptance Model (TAM) (Davis, 1986), the Theory of Planned Behaviour (TPB) (Ajzen, 1985), the Motivational Model (MM) (Ryan and Deci, 2000), Decomposed Theory of Planned Behaviour (DTPB) (Taylor and Todd, 1995), the Model of PC Utilization (MPCU) (Thompson et al, 1991), the Diffusion of Innovation theory (DOI) (Rogers, 2003), and the Social Cognitive Theory (SCT) (Bandura, 1986).
A mixed method approach will be used for this study. Quantitative data will be collected using the survey method while a semi structured interview will also be conducted to get an in depth understanding of the users experience and other factors that may not be evident through the use of quantitative methods. The target population will be bank customers who use social media banking tools and data analysis would be done using statistical techniques using an appropriate software. The study will be exploratory and deductive in nature as an existing conceptual framework will be used (Bryman and Bell, 2007).
Results:
The study will enable us find out what factors determine usage behaviour and what constructs (performance expectancy, effort expectancy, social influence and facilitating conditions) significantly affect the acceptance and adoption of social media banking in both countries.
Future Work:
Future research would investigate cross culture effects on the adoption of social media banking as well as the effects of demographics on the acceptance of social media banking.
References
Ajzen, I. and Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood Cliffs: Prentice-Hall.
Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behaviour (pp. 13–37).
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, N.J.: Prentice-Hall.
Bryman, A., and Bell, E. (2007). Business Research Methods. 2nd edn. Oxford: Oxford University Press, USA.
Davis, F. (1986). Technology acceptance model for empirical testing new end-user information system: theory and results. MIT Sloan School of Management.
Rogers, E. (2003). Diffusion of innovations. New York: Free Press.
Ryan, R., and Deci, E. (2000). Self-Determination Theory and the facilitation of intrinsic motivation, social development and well-being. American psychologist, 55(1), pp.68-78.
Taylor, S., and Todd, P. (1995). Decomposition and cross-over effects in the theory of planned behaviour: A study of consumer adoption intentions. International Journal of Research in Marketing, 12(2), pp.137-155.
Thompson, R., Higgins, C., and Howell, J. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), pp.125-143.
Venkatesh, V., Morris, M., Davis, G., and Davis, F. (2003). User acceptance of information technology: Toward a unified view, MIS Quarterly, 27(3) pp.425-478.
Venkatesh, V., and Zhang, X. (2010). Unified theory of acceptance and use of technology: U.S. vs. China, Journal of Global Information Technology Management. 13(1), pp.5-27.
Social networking sites such as Twitter and Facebook have been shown to function as effective social sensors that can “feel the pulse” of a community. The aim of the current study is to test the feasibility of designing, implementing and evaluating a bespoke social media-enabled intervention that can be effective for sharing and changing knowledge, attitudes and behaviours in meaningful ways to promote public health, specifically with regards to prevention of skin cancer. We present the design and implementation details of the campaign followed by summary findings and analysis.
Background
Research has shown that social networks can mediate the transmission of healthy and unhealthy behaviors in populations; either through selection (Centola, 2010, 2011) or influence (Cha et al, 2010) Social Media (SM) platforms have also been shown to transmit moods, feeling and behaviours (Naveed et al, 2011). There are several studies that have shown the effectiveness of social media in terms of behavioural changes in public health interventions such as in physical activity (Cavallo et al, 2012), sexual health (Bull et al, 2012) and risky sexual behaviours (Jones, Baldwin, & Lewis, 2012). To the best of our knowledge our study is one of the first to use Twitter and Facebook social networking platforms to study public health behaviour while raising awareness about skin cancer and its prevention.
Objective
The study aimed to address the following research questions to support the feasibility assessment: (1) Does SM constitute an acceptable means for delivering public health information in the target population? (2) Are people willing to share personal issues (e.g. health behaviours or attitudes) across a SM platform? (3) What type of SM communication would attract the attention of the target population? (4) Are individuals, organizations, celebrities more likely to tweet or re-tweet messages related to the public health campaign? (5) What are the key factors that motivate users to share messages amongst themselves?
Methods
We began by conducting a survey of 752 households to understand SM usage amongst people in Northern Ireland–the study’s target population. We found Facebook and Twitter to be the two most popular platforms as shown in Table 1. To prepare for the two main phases of the intervention we chose hashtags which broadly differentiated skin cancer awareness from skin surveillance messages respectively. The first Phase which ran from the 1st May – 15th July 2015 contained messages with the #SkinSmartNI, #SkinSavvyNI hashtags. The second Phase ran from 1st August - 30th September 2015 and used the hashtag #KnowYourSkinNI. We chose influencers (including radio, TV weather presenters and celebrities such as music artistes) who we hoped would help diffuse our messages. A coordinated SM event promoting the campaign – a Thunderclap – was designed and then delivered on 1st September 2015 with the aim of creating a trending online meme of the various hashtags used. Figure 1 shows the five message types posted - shocking, story, informative, opportunistic and humorous.
To effectively capture the Twitter data we chose to subscribe to a data provider for the provision of 100% access to the Twitter firehose while Facebook data collected from the analytics dashboard was sufficient for this purpose. However, due to privacy concerns, analysis of Facebook data is limited and beyond the scope of this current paper. JSON data was parsed into CSV and an SQL database for analysis.
Results
In summary, the first phase of the study generated 1,404 interactions comprising tweets, retweets and replies from 366 distinct users while the second phase generated 486 interactions from 217 distinct users. 70% of the messages were sent by users based in the UK. We inferred gender for 65% of the users using “twitterreport” R package. For messages on Twitter we measure message performance in terms of impressions (views) and engagements (clicks). In Table 2 we see the most retweeted messages were “informative” and “humorous” for phases 1 and 2 respectively. We also found no significant difference between promoted and non-promoted messages on both platforms.
Future work
In our ongoing work we examine diffusion of information based on the message topic and the locations of users who propagate the information. Also, we are assessing how the various message types differ in terms of their diffusion. It would be beneficial for assessing SM enabled public health campaigns if finer granularity were obtained using a location inference algorithm (Ajao, Hong, & Weiru, 2015) which may give more location detail on campaign responses at city-level. In addition it would be interesting if future work could accurately infer more demographic characteristics of responders in platforms such as Facebook especially when response volumes were low. These features are crucial in measuring effectiveness of public health interventions.
References
[1] Ajao, O., Hong, J. and Liu, W. (2015) A Survey of Location Inference Techniques on Twitter. Journal of Information Science (Big Social Data Special Issue, Dec 2015) Vol. 41(6) 855–864. DOI: 10.1177/0165551515602847
[2] Bull, S. S., Levine, D. K., Black, S. R., Schmiege, S. J., & Santelli, J. (2012). Social media–delivered sexual health intervention: a cluster randomized controlled trial. American journal of preventive medicine, 43(5), 467-474. DOI: 10.1016/j.amepre.2012.07.022
[3] Cavallo, D. N., Tate, D. F., Ries, A. V., Brown, J. D., DeVellis, R. F., & Ammerman, A. S. (2012). A social media–based physical activity intervention: a randomized controlled trial. American journal of preventive medicine, 43(5), 527-532. DOI: 10.1016/j.amepre.2012.07.019.
[4] Centola, D. (2010) The spread of behavior in an online social network experiment. Science. 329:1194-97. DOI: 10.1126/science.1185231.
[5] Centola, D. (2011) An experimental study of homophily in the adoption of health behavior. Science; 334:1269-72. DOI: 10.1126/science.1207055
[6] Cha, M., Haddadi, H., Benevenuto, F. & Gummadi, P.K. (2010), "Measuring User Influence in Twitter: The Million Follower Fallacy.", International Conference on Web & Social Media, vol. 10, no. 10-17, 30.
[7] Jones, K., Baldwin, K. A., & Lewis, P. R. (2012). The potential influence of a social media intervention on risky sexual behavior and Chlamydia incidence. Journal of community health nursing, 29(2), 106-120. DOI: 10.1080/07370016.2012.670579.
[8] Naveed, N., Gottron, T., Kunegis, J. & Alhadi, A.C. (2011), "Bad news travel fast: A content-based analysis of interestingness on twitter", Proceedings of the 3rd International Web Science Conference ACM, 8. DOI: 10.1145/2527031.2527052
[9] Vega Yon, G. (2015). “twitterreport”: Out-of-the-Box Analysis and Reporting Tools for Twitter. R package version 0.15.8.26. http://github.com/gvegayon/twitterreport [Accessed: 14th April, 2016]
Background:
Many researchers and pundits have claimed that social life has eroded, pointing to different prime causes including industrialization, capitalism, socialism, urbanization, colonialism, and bureaucratization. Recently, some have blamed technology, especially the diffusion of trains, cars, telephones, radios, televisions from diminishing involvement in formally organized groups of parents, veterans, social clubs, and the like (Putnam, 2000), while others have pointed to a supposed lack of authentic connections engendered by digital media (Turkle, 2011; Livingstone, 2008). At the center of this debate is the assumption that ties sustained via computer-mediated communication do not support the mobilization of social support as well as in-person ties (Turkle, 2011; Livingston, 2008). Even if individuals are more connected, it is argued that this increase in ties does not translate into greater networks of social support. Contrary to these claims, our evidence shows that while things are not what they used to be, they have not fallen apart either and social support is exchanged among networks of older Torontonians both on and offline.
Objective:
Much work in the area of social capital suggests that resources can indeed flow through social media such as Facebook (Ellison, Steinfield, & Lampe, 2007) and Twitter (Quan-Haase, Martin, & McCay-Peet, 2015). However, much of this work has collected data from university students and young adults, who have grown up with the internet and mobile devices, the so-called "digital natives" (Prensky, 2001). This study by contrast aims to understand how social support is mobilized within the context of older Canadians’ everyday lives by examining what types of social support older residents of East York exchange with their networks, from whom they receive social support, as well as whom they supply with the same, and finally what role social media plays in facilitating or hindering the mobilization of social support in these networks?
Methods:
The present study represents the fourth wave of data collection that has taken place in East York since 1968 (Coates, Moyer, & Wellman, 1969; Wellman, 1979; Wellman & Wortley, 1990; Wellman et al. 2006) , taking place from November, 2012 to June 2013. The sample frame consisted of 2,321 residents , of which 304 were randomly contacted and 101 agreed to participate. Of these, 41 respondents ranged from 65 to 93 years of age and have been included in this analysis. Employing these participants we investigated the types of social support exchanged, ranging from companionship and the exchange of small and large services, to emotional and financial aid.
Results:
Residents of East York continue to exchange the same types of social support witnessed in previous waves of data collection ranging from emotional aid, small services, large services, and companionship (Wellman, 1979; Wellman & Wortley, 1989; Wellman & Wortley, 1990; Wellman et al. 2006). In contrast, major financial aid was hardly discussed by participants as a type of social support exchanged. Uniquely, we did find that communication is a type of social support that has not been captured in previous typologies and was central to our study, suggesting that for this population of older residents, communication via mobile phones, email, and social media is a kind of social support that is received and exchanged.
As long as the older residents of East York surveyed possessed the necessary skills and means to utilize information and communications technologies (ICTs), they employed them to further connect with their social networks near and far to mobilize social support, maintain ties, plan face-to-face activities, ask for expertise, or engage in casual conversation. Thus ICTs are adding another layer to the mobilization of social support within personal social networks, and therefore potentially increasing happiness and situational satisfaction.
At the same time, this age group shows great appreciation for face-to-face exchanges and consider communication via email and social media an add-on, instead of a substitute. Here email was the most prominent medium employed for communication, while using Facebook was also common, even if respondents did not actively post their opinions online but followed and interacted with friends and family.
For others it brings frustration and feelings of segregation. These respondents often felt a lack of confidence with technology and their low digital skills block them from taking full advantages of the possibilities afforded by these digital technologies. Thus, the older residents of East York could benefit from further support in learning how to make digital media work for them, for their needs.
Future Work:
Respondents considered computer-mediated communication (CMC) to be a form of social support, suggesting that increases in digital communication also increase the exchange of overall social support. Future work can further shed light on ICT use by seniors and their potential reliance on both traditional sources of social support as well as their adoption of social media and social networking platforms. Simultaneously, investigations of the overall social network makeup of all networks within the sample using similar methods will enable researchers to suggest methods to enhance digital literacy, change the features of particular media platforms, and understand the motivations that propel usage by the elderly so as to enable their usage of potential affordances. Likewise an investigation of individual views of privacy, both interpersonal and institutional, alongside further study of technology usage within the sample on the whole may uncover peculiarities of the senior population not yet revealed.
References:
Coates, D. B., Moyer, S., & Wellman, B. (1969). Yorklea study: Symptoms, problems and life events. Canadian Journal of Public Health 60(12), 471-481.
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “Friends:” Social capital and college students’ use of online social setwork sites. Journal of Computer- Mediated Communication, 12(4), 1143−1168.
Livingstone, S. (2008). Taking risky opportunities in youthful content creation: Teenagers' use of social networking sites for intimacy, privacy and self-expression. New Media and Society 10(3), 393-411.
Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon 9(5). http://www.marcprensky.com/writing/Prensky - Digital Natives, Digital Immigrants - Part1.pdf
Putnam, R. (2000). Bowling alone: The collapse and revival of american community. New York, NY: Simon and Schuster.
Quan-Haase, A., Martin, K., & McCay-Peet, L. (2015). Networks of digital humanities scholars: The informational and social uses and gratifications of twitter. Big Data & Society 2(1). http://arxiv.org/abs/1507.02994
Turkle, S. (2011). Alone together. New York, NY: Basic Books.
Wellman, B. (1979). The community question: The intimate networks of East Yorkers. American Journal of Sociology 84(5), 1201-1231.
Wellman, B. & Wortley, S. (1990). Different strokes from different folks: Community ties and social support. American Journal of Sociology 96(3), 558-588.
Wellman, B., & Wortley, S. (1989). Brothers’ keepers: Situating kinship relations in broader networks of social support. Sociological Perspectives, 32(3), 273-306. Wellman, B., Hogan, B., Berg, K., Boase, J., Carrasco, J. A., Côté, R., Kayahara, J., Kennedy, T. L. M., & Tran, P. (2006). Connected lives: The project. In P. Purcell (Ed.), Networked neighborhoods: The online community in context (pp. 157-211). Guildford, UK: Springer.
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Background
Citizen and volunteer networks play an important role in the aftermath of humanitarian crises, particularly in the Global South where formal authorities are not always able to provide an adequate response. Volunteer-driven action groups increasingly use social media-based platforms to enable stakeholders to access, share and broadcast crisis- relevant information. Such platforms are often mobilized by dispersed, relatively well- educated, digitally-literate citizens in an attempt to influence and monitor ongoing relief efforts and raise awareness of the plight of affected communities (Roberts, 2011). These ‘digital humanitarians’ (Meier, 2015) are members of the global digital elite who dedicate themselves to humanitarian causes and seek to champion the interests and needs of local citizens affected by disaster. To date, little research has been carried out into the role of these ‘digital elites’ in shaping crisis communities, to what extent they represent the needs of affected local citizens, and whether/how they succeed in communicating – and transferring - these needs to other networks, particularly networks of formal humanitarian responders (Boersma et al., 2014).
Objective
This study compares social-media enabled crisis communications in the aftermath of the Haiti (2010) and Nepal (2015) earthquakes, toward two complementary goals. First, we explore how digital elites attempt to ‘program’ a social network (Castells, 2009: 45), that is, how they attempt to create online crisis communities with shared identities, shared goals and shared tasks - out of stakeholders with heterogeneous interests and agendas. An important focus here are the in- and exclusions of the voices of different groups of affected citizens on the ground. Second, we analyse how digital elites use social media in an attempt to get government bodies or humanitarian agencies to adopt the goals and tasks of ‘their’ online crisis community. That is, we examine how objectives are ‘switched’ from one social network to another (ibid.) In so doing, we explain how digital elites use social media in their (potential) role as social network ‘programmers’ and ‘switchers’.
Methods
We analyze the online crisis communities using a mixed-methods research design, combining ethnographic methods (Hine, 2008; Tony, 1979) with social network and semantic content analyses (Williams and Shepherd, 2015) of social media data. We contextualize our findings using the historical method.
Results
Our research to date indicates that in both Haiti and Nepal digital elites played a leading role in ‘programming’ and attempts at ‘switching’, with elites in the latter facilitating more ‘bottom-up’ involvement.
Future Work
We carried out fieldwork in Nepal in the immediate aftermath of the 2015 earthquakes and will follow this up with additional fieldwork in March 2016. Furthermore, we will analyse a dataset of online communications between ‘digital humanitarians’ (Meier, 2015) who volunteered their skills and time to create interactive online maps, in an attempt to channel the needs and problems of local affected citizens.
References
Boersma, K., Ferguson, J., Groenewegen, P., and Wolbers, J. (2014) Beyond the Myth of Control: Toward Network Switching in Disaster Management. In: Proceedings of the 11th International ISCRAM Conference (pp. 125-130).
Castells M. (2009). Communication Power. Oxford, New York: Oxford University Press. Hine, C. (2008). Virtual Ethnography: Modes, Varieties, Affordances. The SAGE Handbook
of Online Research Methods, 257-270. Thousand Oaks, CA: Sage.
Meier, P. (2015). Digital humanitarians. How Big Data Is Changing the Face of
Humanitarian Response. Boca Raton: CRC Press.
Roberts, N.C. (2011). Beyond Smokestacks and Silos: Open-Source, Web-Enabled Coordination in Organizations and Networks, Public Administration Review, 71(5): 677- 693.
Tony, W. I. (1979). Anthropology and Disaster Research. Disasters, 3(1): 43–52.
Williams, T. A., and Shepherd, D. A. (2015). Mixed Method Social Network Analysis: Combining Inductive Concept Development, Content Analysis, and Secondary Data for Quantitative Analysis. Organizational Research Methods (online in advance): 1-31. DOI: 10.1177/1094428115610807
The 2015 Nepal earthquakes (NE) began with a 7.8 magnitude earthquake, which hit the nation’s capital, Kathmandu, and its surrounding areas on April 25, 2015. On May 12, 2015 a second major earthquake (of a 7.3 magnitude) struck to the northeast of Kathmandu, affecting various areas in Nepal and regions in Southern China. In the following weeks, continued aftershocks occurred throughout Nepal with short intervals separating them. The earthquakes killed more than 8,000 people, injured more than 23,000, and it is currently estimated that 2.8 million people require humanitarian assistance as a result of being harmed or displaced because of the disaster (Groupe Speciale Mobile Association, 2015). The 2015 NE attracted global attention, and aid organizations from around the world mobilized to help. Yet, given that Nepal is a developing and largely rural country, its ability to respond to and manage such a large-scale crisis was limited. Despite such challenges, some indicate that ICTs were used to facilitate crisis management and response (Groupe Speciale Mobile Association, 2015). Being that ICTs continue to play an increasingly important role in disasters (Burns, 2015), this study seeks to better understand the role of ICTs in the 2015 NE crisis management to potentially inform future uses of ICTs in similar scenarios.
This study strives to contribute to an emerging field of research on the use of ICTs in crisis scenarios through a new case study on the 2015 NE. To do so, this study will gather information from those who leveraged ICTs to facilitate crisis management and response to understand the role of these tools in this specific case. The study is guided by the following research questions:
a) How and by whom were ICTs used in the crisis management and response to the 2015 NE?
b) How did these uses influence the delivery of aid and humanitarian support in the 2015 NE?
c) What challenges and/or risks were involved in the use of ICTs in the 2015 NE crisis response?
d) What were the perceived benefits of the use of ICTs in the 2016 NE crisis response?
e) What are the implications of access to and use of ICTs in the 2015 NE crisis response related to gender?
i. How do gender norms impact a woman’s ability to access and use ICTs in Nepal?
ii. How did gender norms with regards to women’s ability to access and use ICTs in Nepal impact their abilities during the 2015 NE crisis response?
To explore the role of ICTs in the 2015 NE, this study will use a qualitative single-case study research design (e.g., Stake, 1995; Yin, 2014). The case study used for this research will be descriptive in nature. This study will use the process-tracing method (George & Bennett, 2005) to identify the ways in which ICTs influenced crisis management and response in the 2015 NE. The process-tracing method seeks to identify the “intervening casual process—the causal chain and causal mechanisms—between an independent variable (or variables) and the outcomes of the dependent variable” (Ibid, p. 206). This method is defined as the systematic examination of diagnostic evidence selected and analyzed in light of research questions” posed by the investigator (Collier, 2011, p. 823). This method can contribute decisively to social phenomena and evaluating the unfolding of events (Checkel, 2008). It can be applied to research into ICTs and their influences on various social phenomena and activities; therefore, this type of analysis is particularly useful in exploring the influence of ICTs on response to the 2015 NE. This study will use abductive reasoning, as the study will begin with an incomplete set of observations and will seek to proceed to the likeliest possible explanation for the set (Walton, 2005).
The data collection method for this study will be qualitative semi-structured interviews with actors involved in facilitating crisis response and management through the use of ICTs. This may include actors from non-governmental organizations (NGOs), government, and grassroots organizations/efforts. Semi-structured interviews are designed to explore issues in detail with the interviewee, using probes, prompts, and flexible questioning styles (Henn, Weinstein & Foard, 2006). This data collection method is selected for this study because it allows the principal investigator (PI) to pre-design questions guided by the goals of the study, but it will also allow respondents to provide information on their unique accounts and experiences.
A qualitative content analysis of the interview transcripts will be conducted. Content analysis is a “careful, detailed, systematic examination and interpretation of a particular body of material in an effort to identify patterns, themes, biases, and meanings” (Berg, 2007, p. 248). This form of analysis is used in various disciplines for a multitude of purposes; it is mainly a coding operation and data interpreting process (e.g., Mayring, 2004; Schreier, 2012). The analysis will examine both manifest and latent content found in the data to understand the surface structure of the messages as well as their deep structural meanings (Berg, 2007). Thus, the study will examine exactly what the narratives found in the text may seek to do or mean based on the ways different ideas and concepts are expressed through the language of the text (Berg, 2011). This will be achieved through coding of themes and sub-themes expressed in the transcripts (Saldaña, 2015).
Given the case study research design, the study uses purposive and snowball sampling techniques, which are both nonprobability sampling strategies.
It is hoped that the report may be particularly useful to those who work at NGOs and government organizations involved in the management of and response to crises and disasters. This research will also seek to contribute to knowledge pertaining to the ways in which ICTs can be leveraged to improve crisis response and management.
References
Berg, Bruce L. (2007). An introduction to content analysis. In Mahmoud Eid and Martine Legacé (Eds.), Communication research methods: Quantitative and qualitative approaches (pp. 247-284). Boston, MA: Pearson.
Berg, Bruce L. (2011). An introduction to content analysis. In Mahmoud Eid (Ed.), Research methods in communication (pp. 209-236). Boston, MA: Pearson.
Burns, Ryan. (2015). Rethinking big data in digital humanitarianism: Practices, epistemologies, and social relations. GeoJournal, 80(4), 477-490.
Checkel, Jeffrey T. (2008). Process tracing. In Audie Klotz and Deepa Prakash (Eds.), Qualitative methods in international relations (pp. 114-127). London: Palgrave McMillian UK.
Collier, David. (2011). Understanding process tracing. Political Science and Politics, 44(4), 823-830.
George, Alexander L. & Bennet, Andrew. (2005). Case studies and theory development in the social sciences. Cambridge, MA: MIT Press.
Groupe Speciale Mobile Association. (2015). Disaster response – Nepal earthquake response and recovery overview. Retrieved January 6, 2016, from http://www.gsma.com/mobilefordevelopment/programme/disaster-response/disaster-response-nepal-earthquake-response-and-recovery-overview/.
Henn, Matt, Weinstein, Mark & Foard, Nick. (2006). A short introduction to social research. London: Sage.
Mayring, Phillip. (2004). Qualitative content analysis. In Uwe Flick, Ernst von Kardoff, and Ines Steinke (Eds.), A companion to qualitative research (pp. 266-269). London: Sage.
Saldaña, Johnny. (2015). The coding manual for qualitative researchers. Los Angeles: Sage.
Schreier, Margrit. (2012). Qualitative content analysis in practice. Los Angeles, CA: Sage.
Stake, Robert E. (1995). The art of case study research. Thousand Oaks, CA: Sage.
Walton, Douglas. (2005). Abductive reasoning. Tuscaloosa, AL: University of Alabama Press
Yin, Robert. (2014). Case study research: Design and methods. Los Angeles, CA: Sage.
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Abstract
As social media data mining becomes more and more ordinary, as we post, our posts get mined and this process gets repeated, new data relations emerge. These new data relations are characterised by a widespread desire for numbers. To talk about a desire for numbers, rather than a trust in numbers (Porter 1995), makes it possible to account for some of the contradictions that accompany the becoming-ordinary of social media data, such as hunger for and evangelism about but also frustration in and criticism of data and data mining. This widespread desire for numbers brings with it some troubling consequences: it becomes increasingly difficult to discuss problems with social media data mining despite recognition of them amongst data miners, and it has effects of all kinds on work and workers. Despite these problems, and because of the ubiquity of data and data mining, the possibility of doing good with data (and with data mining) endures. Together, these and other contradictory tendencies – the persistence of some old concerns; the emergence of new ones; data power and challenges to it – constitute the new data relations that emerge when social media data are ordinary. In this presentation, I illustrate this argument by drawing on action research with public sector organisations, interviews with commercial social media insights companies and their clients, focus groups with social media users and other research.
BIO
Helen Kennedy is Professor of Digital Society at the University of Sheffield. She has recently been researching what happens when social media data mining becomes widespread – this research will be published as a monograph entitled Post, Mine, Repeat: social media data mining becomes ordinary (Palgrave Macmillan, 2016, was funded by an AHRC Fellowship). Current research includes Seeing Data (www.seeingdata.org), which explores how non-experts relate to data visualisations (funded by an AHRC Digital Transformation large grant). Previous research has traversed digital media landscapes, covering topics including: homepages, identity and representation; race, class, gender inequality; learning disability and web accessibility; and web design and other creative digital work. She is currently interested in critical approaches to big data and data visualisation, how to make data more accessible to ordinary citizens, and whether data matter to people.
Background:
Recent scholarship in Library and Information Studies (LIS) reveals that commercial social media services such as Facebook and Twitter are used by a vast majority of university libraries in the United States, Canada and elsewhere (for example, Boateng and Liu 2014). To date, few studies have considered critically the implications of widespread library adoption of social media tools and services. In particular, the impact that social media use by libraries may have on patron privacy remains underexplored. Michael Zimmer (2013), for example, has shown that only a small minority of articles on social media and libraries address privacy in a meaningful way. Zimmer also identifies what he describes as a “policy vacuum” on matters relating to patron privacy and library use of social media tools. More recently, Sarah Shik Lamdan (2015) has argued that librarians should play a lead role in advocating for social media terms of service that value users’ privacy rights.
Objective:
This paper critically examines privacy implications of commercial social media from the perspective of the academic library. Libraries have a long tradition of protecting patron privacy. Privacy is a core library value that informs and underpins much of the work of librarians, including the protection and promotion of intellectual freedom. The paper investigates whether library adoption of commercial social media signals acceptance of the idea that erosion of patron privacy is a reasonable and unavoidable tradeoff for the benefits of social media. It also considers how library use of alternatives to commercial social media platforms may better enable libraries to maintain their role as defenders of patron privacy.
Methods:
Building on Christian Fuchs’ analysis of the political economy of social media and his idea of privacy as a “collective right of dominated and exploited groups that need to be protected from corporate domination” (2014), this paper situates library practices surrounding social media within contemporary sociopolitical contexts and power relations. It also considers scholarly work on privacy and surveillance from related disciplines, including work examining the corporate control of privacy and the role of surveillance as technology of governance.
Results:
Revelations about expansive government agency surveillance and corporate complicity in this surveillance point to a continuing need for the library’s role as defender of patron privacy. Similarly, as sites of teaching and learning, libraries can help foster understanding of the relationship between privacy and autonomy and of the important role these play in democratic citizenship. This paper concludes that library use of commercial social media, in the absence of well-developed policy and terms of service that respect user privacy, can conflict with and undermine library and librarian efforts to contest threats to privacy both within and outside the library.
Future Work:
Further research is needed to assess critically the impact that social media may have on the longstanding role of libraries as defenders of patron privacy. In particular, additional research is needed to examine library use and promotion of alternatives to commercial social media platforms.
References Cited in the Abstract:
Boateng, F., & Liu, Y. Q. (2014). Web 2.0 applications' usage and trends in top US academic libraries. Library Hi Tech, 32(1), 120-138.
Fuchs, C. (2014). Social Media: A Critical Introduction. Los Angeles, Sage.
Lamdan, S. S. (2015). Social Media Privacy: A Rallying Cry to Librarians. Library Quarterly, 85(3), 261-277.
Zimmer, M. (2013). Assessing the Treatment of Patron Privacy in Library 2.0 Literature. Information Technology & Libraries, 32(2), 29-41.
Background:
Digital privacy research suggests that individuals view personal information disclosure negatively (Ellison et al 2011). However, social media users repeatedly share personal information with individuals and commercial organisations (Kang et al 2014). Indeed, consumer engagement research indicates that users actively seek social media connections with brand fan pages in return for a range of benefits (Brodie et al 2011, de Vries et al 2012). We seek to understand whether the extent of information disclosure to an organisation is related to the benefit being sought. Our work tests whether brand engagement motivations meaningfully classify social media users and then examines the extent to which information disclosure varies between user classifications.
Objective:
To apply Uses and Gratifications Theory (Katz et al 1973) to identify the motivations behind social media users’ engagement with brands and relate these motivations to differences in information disclosure.
Methods:
We surveyed 400 college students and achieved a sample of 249. Validated scales were adapted to the context of social media brand engagement: Smock et al (2011) for Facebook Uses and Gratifications and Milne et al (2004) for personal information disclosure. Responses were measured on a 7-Point Likert scale, where 1 is “Strongly Disagree” and 7 is “Strongly Agree”. There were three stages of analysis: (1) an exploratory factor analysis to identify the dimensions of brand engagement motivation (2) a hierarchical cluster analysis to classify social media users according to motivations for engaging with brands; (3) an ANOVA to identify differences in information disclosure between user classifications.
Results: We identify three motivational dimensions for social media brand engagement: ‘Better Treatment’, ‘Brand Connection’ and ‘Brand Entertainment’. Using these motivational dimensions we classify users into three segments: ‘Brand Skeptics’, ‘Brand Value Seekers’ and ‘Brand Enthusiasts’. Results show that Brand Skeptics are not motivated by brand entertainment, brand connections or better treatment and provide evidence of scepticism towards online commercial advances (see Grant 2005). Brand Value Seekers are motivated by financial reward (commercial deals and better prices) and do not seek brand entertainment or brand connection. Brand Enthusiasts are motivated by brand entertainment and brand connection. We find a relationship between brand engagement motivations and the nature of information disclosure. Specifically that Brand Value Seekers are more likely to engage in privacy protection behaviors such as blocking requests for contact, changing default privacy settings and excluding certain personal information from the exchange. The findings have implications for the information solicitation strategies used by brands within social media. Our work shows that offering financial reward will result in limited disclosure whilst offering entertainment and a connection to the brand will gain greater access to information.
Future Work:
Results reveal salient social media user segments with different motivations for engaging with commercial organisations that relate to the extent of information disclosure. We will apply these insights to examine brand engagement motivations and information disclosure among users from different cultures and of different ages.
References:
Brodie, R. J., Ilic, A., Juric, B., & Hollebeek, L. (2013). Consumer engagement in a virtual brand community: An exploratory analysis. 66 (1) Journal of Business Research. pp 105-114
De Vries, L., Gensler, S. and Leeflang, P.S., (2012), Popularity of brand posts on brand fan pages: An investigation of the effects of social media marketing. Journal of Interactive Marketing, 26(2), 83-91.
Ellison, N.B., Vitak, J., Steinfield, C., Gray, R. and Lampe, C., (2011) Negotiating privacy concerns and social capital needs in a social media environment. In Privacy online (pp. 19-32). Springer Berlin Heidelberg.
Grant, I. (2005). Young Peoples’ Relationships with Online Marketing Practices: An Intrusion Too Far?. Journal of Marketing Management, 21(5/6), 607-624.
Ibrahim, Y., (2008). The new risk communities: Social networking sites and risk. International Journal of Media & Cultural Politics, 4(2), 245-253.
Kang, J., Tang, L. and Fiore, A.M., (2014). Enhancing consumer–brand relationships on restaurant Facebook fan pages: Maximizing consumer benefits and increasing active participation. International Journal of Hospitality Management, 36 (Jan), 145-155.
Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. Public Opinion Quarterly, 37(4), 509-523.
Milne, G. R., Rohm, A. J., & Bahl, S. (2004). Consumers’ protection of online privacy and identity. Journal of Consumer Affairs, 38(2), 217-232
Smock, A. D., Ellison, N. B., Lampe, C., & Wohn, D. Y. (2011). Facebook as a toolkit: A uses and gratification approach to unbundling feature use. Computers in Human Behavior, 27(6), 2322-2329.
Tufekci, Z. (2008). Can you see me now? Audience and disclosure regulation in online social network sites. Bulletin of Science, Technology & Society, 28(1), 20-36.
This study analyzes the motivations of Social Networking Sites (SNS) users to disclose personally identifiable information on SNS. The rationale for the study stems from the fact that information disclosure is critical to sustaining the popularity and value of SNS. Indeed, without massive production and consumption of identified personal information, SNS will not be able to fulfill users’ attentiveness needed to secure their loyalty (Chen, 2012). Because information disclosure is of strategic value on SNSs, SNS providers employ various tactics to encourage users to disclose information about themselves.
A variety of approaches have been used to explain an individual’s willingness to disclose personal information on SNS. It has been reported that anticipation of benefits, such as enjoyment and social acceptance, motivates users to disclose personal information (e.g. Sledgianowski and Kulviwat, 2008). However, it was noted that the choice to disclose is also affected by the information owner’s perceptions of risks, such as harassment, tracking of browsing history, third party usage of personal data and identity theft. Thus, while perceptions of usefulness offer people a reason to disclose personal information on SNS, perceptions of risk tend to play the opposite role. Acknowledging the push and pull between such conflicting elements, researches introduced the privacy-calculus concept to denote the risk-benefit assessment that users make in deciding how much to disclose (e.g. Dinev et al., 2006).
While providing valuable insight into the effects of risk-benefit assessment on self -disclosure behavior, most of the existing studies overlook the significant role played by reciprocal features of SNS to users’ disclosure motivations. The present study, aims to understand how users’ ability to view and traverse other users’ actions, as well as the rewards and snags they receive, impinge on their privacy-calculus and resulting self- disclosure behavior. Recognizing that SNS provide an environment conducive to social observation and social learning (Zhang and Daugherty, 2009), we develop a model of self-disclosure that draws from the theory of observational learning (Bandura, 2009) and the concept of privacy calculus (e.g. Dinev et al., 2006).
We proposed the following hypotheses:
H1. Perceived gains tied to SD behavior will be positively associated to SD behavior online.
H2. Perceived risks tied to SD behavior will be negatively associated to SD behavior online.
H3. Perceived SD by others will be positively associated to SD behavior online.
H4. Others’ perceived gains due to SD behavior would be positively associated to ones’ perceived gains due to SD.
H5. Others’ perceived risks due to SD behavior would be positively associated to ones’ perceived risks due to SD.
H6. Others’ perceived gains due to SD behavior would have a mediated influence on one’s SD behavior.
H7. Others’ perceived risks due to SD behavior would have a mediated influence on one’s SD behavior.
We empirically tested our model and associated hypotheses using data we collected through an online survey (N=742 Jewish Israeli Facebook users). The sample was designed to be representative of the Jewish Israeli population of Facebook. We began our analysis with a general assessment of the privacy calculus. The distribution of gains and risks was fairly normal and centered around a small negative mean (M=-2.5, SD=7.7), we found that for themselves, people see self disclosure [herein after: SD] as an activity that involves both risks and benefits. For their Facebook friends [hereinafter: ‘others’], the result was almost identical (M=-.55, SD=7.5). The difference between perception of self and others is small but significant (t1,592=-12.0, p<0.01). In addition, we wanted to test whether people tied SD to risks and gains. That is, if people understand that in order to benefit from SNS, SD is required, but also, that SD on SNS expose them to risks. We found a positive relation between SD behavior and perception of gains, both in the case of ‘self’ and ‘others’. When it comes to risks, however, the pattern is slightly more complex. We found no significant relation between one’s SD behavior and perception of risk. In the case of perception of other’s SD behavior, perceived risks are positively tied to SD behavior. The correlations found suggest that in general, people connect SD behavior to both risks and gains. However, the relations are more noticeable in the case of gains, compared to risks. Be that as it may, in all cases the relations are positive. The pattern found supports the logic of the privacy calculus concept. To test our hypotheses we used SEM. The model was assessed with SD actions and sharing information creating a latent variable of SD behavior, both for self and other. The theoretical model yielded satisfactory results in terms of goodness of fit indices. We obtained a chi-square to df ratio (CMIN/DF) of 1.52. The model fits the data extremely well (χ2 = 24.0, df = 26, p = .58; RMSEA = .00, CFI = .998).
Our hypotheses were confirmed with one exception. With respect to gains: Other’s perceived gains were positively associated with perceived gains for self, which were, in turn, positively associated with SD behavior. In addition, other’s perceived gains has a positive and significant indirect effect on SD behavior. As for risks: perceived risks to others were positively associated with perceived risks to self. Others’ former experience - that is, whether or not others were harmed - was associated with perceived risks to self, yet the relation was negative. Contrary to our hypothesis perceived risks to self had no bearing on SD behavior. Importantly, being harmed in the past was positively associated with SD behavior. More so, although perceived risks to self had no effect on SD behavior, perceived risks to others did – negative relation between the two was found. Lastly, perceived SD behaviors of others was positively associated with SD behavior.
The model we developed enabled us to observe a net positive effects of perceived risk and perceived benefits on personal information disclosure. We found that information regarding SD behaviors of one’s Facebook friends, and the rewards they receive, have a powerful effect on one’s benefits perceptions and by implication on his/hers disclosure behavior. We thus argue that voluntary disclosure on SNS is tied to the usefulness that users attribute to online social networking activities – a perception that is based on their own experiences as well as on the experiences of others actors whom they constantly observe.
References
Bandura, A. (Ed.). (2009 [1974]). Psychological modeling: Conflicting theories. Transaction Publishers.
Chen, R. (2013). Living a private life in public social networks: An exploration of member self-disclosure. Decision Support Systems, 55(3): 661-668.
Sledgianowski, D. & Kulviwat, S. "Social Network Sites: Antecedents of User Adoption and Usage" (2008). AMCIS 2008 Proceedings. Paper 83.
Retrieved from: http://aisel.aisnet.org/amcis2008/83
Dinev, T., Bellotto, M., Hart, P., Russo, V., Serra, I., & Colautti, C. (2006). Privacy calculus model in e-commerce–a study of Italy and the United States. European Journal of Information Systems, 15(4), 389-402.
Zhang, J., & Daugherty, T. (2009). Third-person effect and social networking: implications for online marketing and word-of-mouth communication. American Journal of Business, 24(2), 53-64.Background:
Facebook is a successful advertising platform as it offers profound advertising customization, due to extensive processing of user information (eMarketer, 2015; Facebook, 2015). Although key to Facebook’s business model, advertising is not the main motivation for its users to access the platform (Wilson, Gosling, & Graham, 2012). Users have to “accept” the presence of advertising alongside the content for which they visit Facebook. Hence, user acceptance is a crucial factor for both the advertiser and the social networking site.
Objective:
We investigate the impact of different choices and options in the creation of Facebook ads, related to the use of personal data (e.g. sensitivity of personal data) and advertising place (e.g. ad location), on user acceptance. Six factors were identified, based on theory and practice, and implemented in fictitious advertisements on a mock Facebook page. Each factor had two or three possible manifestations:
Factors related to the use of personal data
1) Social context: the ad either included a message “[A friend] likes [brand]” or not.
2) Data collector’s perceived risk: An energy company (pre-tested high perceived risk), and a movie company (pre-tested low perceived risk).
3) Data use transparency: a message about data use was either included in the ad or not.
4) Sensitivity of personal data in the ad: “no personal data”, “low sensitive”, or “high sensitive” personal data.
Factors related to advertising place
5) Ad location: “newsfeed”, a person’s “timeline”, or “fan page of an unrelated brand”.
6) Ad placement on the page: “left sidebar”, “right sidebar”, or “message stream”.
Product involvement, an influential processing variable, was included as a moderator (Dens & De Pelsmacker, 2010; Lee, Kim, & Sundar, 2015).
Methods:
An online full factorial survey was completed by 409 Facebook users (53% response rate), aged 25 to 55 years (M = 40.18, SD = 8.9, 54.5% female). By randomizing the manifestations of each factor, 217 (3*3*3*2*2*2) vignette-combinations were created. A sample of 100 vignettes was drawn and was divided over 20 decks. Each respondent was randomly assigned to one 5-vignette deck. For each vignette they indicated their user acceptance (7-point, Cronbach's alpha = .939).
Results:
Multilevel analysis was performed with the six factors as independent variables and user acceptance as the dependent (Auspurg & Hinz, 2014). Only a significant effect of placement on user acceptance was found. The right sidebar placement (M = 3.70) was better accepted than the message stream placement (b = -.13, t(1660.48) = 2.19, p = .029) and the left sidebar placement (b = -.18, t(1659.61) = -3.15, p = .002), which did not differ. Interaction analyses indicated product involvement as a moderator. A multilevel analysis was performed on both the low and high involvement group. Respondents scoring low on product involvement, accepted ads in the right sidebar placement best (M = 3.60), followed by the left sidebar placement (b = -.22, t(756.12) = -2.44, p = .015) and the message stream placement (b = -.47, t(766.29) = -5.05, p < .001). The high product involvement group accepted the message stream placement best (M = 3.98), followed by the right sidebar placement (b = -.15, t(900.77) = -1.94, p = .052), and the left sidebar placement (b = -.31, t(901.22) = -4.04, p < .001). In conclusion, user acceptance is primarily driven by ad placement. Yet, its influence depends on the degree of product involvement. High product involvement is related to higher acceptance of ads with a prominent placement. Ads for low involved products are better accepted when shown in the sidebar. These findings can be related to differences in processing of (native) in-stream ads compared to (banner) sidebar ads.
Future Work:
The results are the basis for more in-depth experimental analysis on the role of advertising placement on the acceptance of Facebook advertising, and the influence of intrusiveness as a mediator. A follow-up experiment is carried out and a full paper is expected in summer 2016.
References:
Auspurg, K., & Hinz, T. (2014). Factorial Survey Experiments. SAGE Publications.
Dens, N., & De Pelsmacker, P. (2010). Consumer response to different advertising appeals for new products: The moderating influence of branding strategy and product category involvement. Journal of Brand Management, 18(1), 50–65. http://doi.org/10.1057/bm.2010.22
eMarketer. (2015, March). Facebook and Twitter Will Take 33% Share of US Digital Display Market by 2017 - eMarketer. Retrieved December 18, 2015, from http://www.emarketer.com/Article/Facebook-Twitter-Will-Take-33-Share-of-US-Digital-Display-Market-by-2017/1012274
Facebook. (2015). About Advertising on Facebook. Retrieved December 18, 2015, from https://www.facebook.com/about/ads
Jung, J., Shim, S. W., Jin, H. S., & Khang, H. (2015). Factors affecting attitudes and behavioural intention towards social networking advertising: a case of Facebook users in South Korea. International Journal of Advertising, 35(2), 248–265. http://doi.org/10.1080/02650487.2015.1014777
Lee, S., Kim, K. J., & Sundar, S. S. (2015). Customization in location-based advertising: Effects of tailoring source, locational congruity, and product involvement on ad attitudes. Computers in Human Behavior, 51, Part A, 336–343. http://doi.org/10.1016/j.chb.2015.04.049
Wilson, R. E., Gosling, S. D., & Graham, L. T. (2012). A Review of Facebook Research in the Social Sciences. Perspectives on Psychological Science, 7(3), 203–220. http://doi.org/10.1177/1745691612442904
Background:
Besides all Web 2.0 facilities for sharing self-content and SMS gratifications for this practice, this study aims to discuss if Facebook users are stuck by self-censorship and silence. Many scholars argue how issues such as context collapse, privacy management, surveillance awareness and illiteracy could be related to self-information disclosures restrictions, bringing side effects to performances online. Combining a set of desk research and analysis of empirical studies on the topic, we could propose users fell less comfortable to talk about themselves and are more likely to perform their identity by consuming, liking and sharing third parties performances. In fact, a 21% decline in original personal sharing (from mid-2014 to mid-2015) was recently reported on Facebook[1]. Our contribution is to analyse why people decide to like and share the things they do through the Spiral of Silence theory and dynamics (NOELLE-NEUMANN, 2001). Relating public opinion to friends opinion and how Facebook make it visible, actors' choices could be defined not only by affinity or admiration, but also under the influence of these performances' audience measures. As described in the spiral of silence model, because some content seems to spread among their social network, actors could assume that they reflect the majority opinion. Thus, the fear of being isolated could motivate their endorsements and consumption. This hypothesis drives us to the majority illusion phenomena (LERMAN, YAN, WU, 2015) and how Facebook might transform visibility into silence.
Objective:
Verify if the Spiral of Silence phenomenon can be observed on Facebook and how is it impacts on users self-censorship and self-presentation.
Results:
As a work-in-progress paper, we do not allow conclusive results. However, based on the desk research carried out, we found out that:
• 44% of Facebook users “like” content posted by their friends at least once a day, with 29% doing so several times per day. 31% comment on other people’s photos on a daily basis, with 15% doing so several times per day. 19% send private Facebook messages to their friends on a daily basis, with 10% sending these messages multiple times per day. 10% change or update their own status on Facebook on a daily basis, with 4% updating their status several times per day. Some 25% of Facebook users say that they never change or update their own Facebook status[2] (transcription from original text).
• 71% of the 3.9 million users in this sample self-censored at least one post or comment over the course of 17 days, confirming that self-censorship is common. Posts are censored more than comments (33% vs. 13%). Also, we found that decisions to self-censor content strongly affected by a user’s perception of audience[3] (transcription from original text).
• 20% of Facebook users like pages because they see friends already did it[4].
Future Work:
Apply a survey to observe: a) the effect of "opinion climate" over Facebook users likes and shares; b) the influence of friends' reputation over the consumption and interactions made online.
Conduct indeep interviews with some of the survey participants to deepen the discussion why people like and share what they do on Facebook.
References:
LERMAN, K., YAN, X., WU, X. (2015). The Majority Illusion in Social Networks. USC Information Sciences Institute. http://arxiv.org/abs/1506.03022
NOELLE-NEUMANN, E. (2013). La espiral del silencio - Opinión pública: nuestra piel social. Barcelona: Editora Vozes.
[1] Bloomberg Technology (2016). Facebook wants you to post more about yourself. <http://www.bloomberg.com/news/articles/2016-04-07/facebook-said-to-face-decline-in-people-posting-personal-content?platform=hootsuite>. Acess on Access on 04/11/16.
[2] Pew Research Center (2014). http://www.pewresearch.org/fact-tank/2014/02/03/6-new-facts-about-facebook/. Access on 09/28/15.
[3] DAS, Sauvik and KRAMER, Adam (2003). Self-Censorship on Facebook. Association for the Advancement of Artificial Intelligence (www.aaai.org). http://sauvik.me/system/papers/pdfs/000/000/004/original/self-censorship_on_facebook_cameraready.pdf?1369713003. Access on 09/28/15.
[4] Synapse.com (2013). Why consumers become brand fans. http://www.syncapse.com/why-consumers-become-brand-fans/#.Vg7UfHvDaOX. Access on 10/02/15.
Background:
In recent years there has been increasing scholarly interest on the use of social media (e.g. Facebook, Twitter) by law enforcement agencies to reach out to and engage with citizens, such as in the United States (Brainard & Edlins, 2015), Canada (Schneider, 2014), and United Kingdom (Crump, 2011). These efforts are part of strategic efforts to engage in police “image work” so as to reinforce perceptions of authority, legitimacy, and credibility.
This study focuses on the Facebook group page of the Hong Kong Police Force (HKPF), established in October 5th, 2015. The launch came one week after the one- year anniversary of the Umbrella Movement in Hong Kong where the HKPF was widely criticized for the firing of teargas on protesters. Moreover, citizen’s satisfaction with the police, dubbed as “Asia’s finest”, has fallen from 81% in 2007 to 50% in 2015 (HKUPOP, 2015). Most of the Umbrella Movement protesters were young, a demographic that is also the heaviest users of social media. Thus, the prospects for civil and rational discourse on the HKPF Facebook page did not appear promising. In fact, it may even become a site of discursive contestation and a “critical-reflexive space” for counter discourses to be disseminated by users against those in power (Dahlberg, 2011). This is especially the case for Hong Kong, where protests for greater democracy have in recent years become more confrontational and provocative (Garrett & Ho, 2014).
Objective:
This study examines:
Thus, this study takes a step further in the literature by actually examining the content of the messages.
Methods:
The study uses a hybrid approach that combines big data with discourse/content analysis (Lewis, Zamith, & Hermida, 2013). First, all HKPD Facebook posts is extracted using Facepager (Keyling & Jünger, 2013). Then, systematic concordance analyses using AntConc (Anthony, 2014) are conducted in order to quantity the most common words/phrases and qualitatively classify the different genres of discourse. This study examines the prevalence and sustainability of counterdiscourses derived from the ten ‘statement’ posts. The rationale is that these posts generally have the highest level of user engagement and comprise 40% of all user comments. They are the most authoritative in the sense that they represent the ‘voice’ of the HKPF leadership. The negatively of user comments in the first two days of the HKPF Facebook page was widely reported by the Hong Kong media.
Results:
Preliminary concordance analyses of key words and subsequent qualitative categorizing and analyses led to some findings:
The longer-term goals of the project are to analyze the messages longitudinally to have a better understanding of the posts, user types, and related intertextual political discourse.
References:
Anthony, L. (2014). AntConc (Version 3.4.3). Tokyo, Japan: Waseda University. Retrieved from http://www.laurenceanthony.net/
Brainard, L., & Edlins, M. (2015). Top 10 U.S. Municipal Police Departments and Their Social Media Usage. American Review of Public Administration, 45(6), 728-745.
Cammaerts, B. (2007). Jamming the Political: Beyond Counter-hegemonic Practices. Continuum: Journal of Media & Cultural Studies, 21(2), 71-90.
Crump, J. (2011). What Are the Police Doing on Twitter? Social Media, the Police and the Public. Policy & Internet, 3(4).
Dahlberg, L. (2011). Re-constructing digital democracy: An outline of four ‘positions. New Media & Society, 17(1), 855-872
Garrett, D., & Ho, W.-c. (2014). Hong Kong at the brink: Emerging forms of political participation in the new social movement. In J. Y. S. Cheng (Ed.), New trends in Hong Kong's political participation (pp. 347-384). Hong Kong: City University of Hong Kong Press.
Harold, C. (2004). Pranking rhetoric: "culture jamming" as media activism. Critical Studies in Media Communication, 21(3), 189-211.
HKUPOP. (2015). People's Satisfaction with the Performance of the Hong Kong Police Force. Retrieved Jun 27, 2013, from https://www.hkupop.hku.hk/english/popexpress/hkpolice/halfyr/hkpolice_halfyr_char t.html
Keyling, T., & Jünger, J. (2013). Facepager. An application for generic data retrieval through APIs. from https://github.com/strohne/Facepager
Lewis, S. C., Zamith, R., & Hermida, A. (2013). Content Analysis in an Era of Big Data: A Hybrid Approach to Computational and Manual Methods. Journal of Broadcasting & Electronic Media, 57(1), 34-52.
Schneider, C. J. (2014). Police presentational strategies on Twitter in Canada. Policing and Society.
Background:
It is well-established that conservatives report higher life satisfaction than liberals (Napier & Jost, 2008; Alesina, Di Tella, & MacCulloch, 2004; Taylor, Funk, & Craighill, 2006), even when controlling for potential confounds such as household income, age, education, and numerous other factors. Although the finding that conservatives tend to seem happier than liberals is not new, our research contributes to the existing body of literature in two ways. First, the detection of this trend in microblogs is novel, as previous findings were based on surveys about life-satisfaction. And second, by analyzing the content of the microblogs, we gain insight into the reality behind this well-known trend. Further plans for research are also discussed.
Objective:
We investigate whether these life-satisfaction differences are detectable between Facebook status updates of liberal versus conservative Americans.
Methods:
Our source of Facebook updates was www.myPersonality.org, which provides over 4,000,000 individuals’ Facebook profile information (Kosinski et al., 2015). The myPersonality project is affiliated with 250 researchers and over 32 publications (e.g., Youyou, Kosinski & Stillwell, 2015; Lamiotte & Kosinski, 2014).
The dataset of 16,906 users’ self-proclaimed political affiliations in the myPersonality database is comprised of 144 categories because Facebook does not have any constraints on what can be entered in this field. For some of the affiliations (e.g., “democrat”), a user’s status as liberal is clear. However, some are less objectively categorized, so we had 13 people interpret the affiliations. We narrowed the users into 3 types of voters: conservatives (3,622), liberals (5,333), and either (2,496). Probable non-voters were excluded. Rationale for this will be explained in the presentation.
Example affiliations in each category:
Liberal - Obama baby, Democrat, Liberal
Conservative - Conservative, Nobama, Republican
Either - Depends, I don’t know, Middle of the road
Neither - Who cares?, Bullshit, Anarchy
We then compared groups using Linguistic Analyisis and Word Count (LIWC) emotionality data (Tausczik & Pennebaker, 2010). LIWC measures a corpus’ emotionality based on word frequency. For example, positive emotion words such as love, nice, and sweet increase a body of text’s positive emotion score, whereas hurt, ugly, and nasty increase negative emotion scores. We compared these two LIWC scores for our users in the three voting groups: liberal, conservative, and either.
Results:
An ANOVA comparing positive and negative emotion words in status updates of conservatives, liberals, and swing voters showed significant differences for positive emotions F(2, 11,448) = 25.93, p < 0.001 and for negative emotions F(2, 11,448) = 25.93, p < 0.001. Fisher LSD post-hoc analyses showed that liberals and conservatives were significantly different in both ANOVAs. The “either” group did not have any significant differences.
Future Work:
There are a number of possible explanations for why liberals are less happy than conservatives. Although these possibilities have been discussed in previous literature, no conclusions have yet been made. One possibility is that one tends to associate more with members of the same political party. Over time, the peer group’s affect could converge, causing this emotional heterogeneity between groups. Another alternative is that the worldview that leads one to become liberal or conservative is at the root of the language differences we have found. If that is the case, the content of the status updates could provide more insight, which will also be discussed in the presentation.
Although numerous other studies have found that liberals tend to be less happy than conservatives, to our knowledge, this is the first study to show that the everyday Facebook language of liberals versus conservatives reflects the previously found affect differences between groups. We plan to continue this research with empirical studies to determine whether we can reverse the effect. If the effect is reversible, that would provide evidence that the peer groups are driving the language. We will also continue our text analysis by evaluating the content of the updates, which will lead to a deeper understanding of the types of positive and negative statements being made by each group. These findings could influence politics, commerce, and social media design.
References:
Alesina, A., Di Tella, R., & MacCulloch, R. (2004). Inequality and happiness: are Europeans and Americans different? Journal of Public Economics, 88(9-10), 2009–2042. http://doi.org/10.1016/j.jpubeco.2003.07.006
Kosinski, M., Matz, S., Gosling, S., Popov, V. & Stillwell, D. (2015). Facebook as a social science research tool: Opportunities, challenges, ethical considerations and practical guidelines. American Psychologist, 70(6), 543-556.
Lambiotte, R. & Kosinski, M. (2014). Tracking the digital footprints of personality. Proceedings of the Institute of Electrical and Electronics Engineers (IEEE), 102(12), 1934-1939.
Napier, J. L., & Jost, J. T. (2008). Why Are Conservatives Happier Than Liberals? Psychological Science, 19(6), 565–572. http://doi.org/10.1111/j.1467-9280.2008.02124.x
Tausczik & Pennebaker, J.W. (2010). The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology 29(1), 24-54.
Taylor, P., Funk, C., & Craighill, P. (2006). Are we happy yet? Pew Research Center social trends report. (M. A. Motes, Ed.) PloS one (8). http://doi.org/10.1371/journal.pone.0083143
Youyou, W., Kosinski, M., & Stillwell, D. (2015). Computer-based personality judgments are more accurate than those made by humans. Proceedings Of The National Academy Of Sciences (PNAS), 112(4), 1036-1040. http://www.pnas.org/content/112/4/1036.full
Background:
On 1st January 2014 restrictions were lifted on the migration of Romanians and Bulgarians to the UK. Leading up to this date and since then, heated debate has ensued about the impact of this migration. Discourses and images of the country being swamped by this new ‘other’ have proliferated.
Objective:
Our aim is to investigate how these debates were discursively constructed over the micro-blogging platform Twitter over a five month period October 1, 2013 and March 1, 2014. We draw on understandings of how the nation and national identity is reproduced in established nation-states of the ‘West. Billig (1995) sought to draw our attention to the familiar, habitual, unconscious ways in which the nation is flagged in countries like Britain, which he terms ‘banal nationalism’. But in recent years Billig has been criticized for maintaining a separation between ‘banal’ and ‘hot’ nationalism. Skey (2009) and Jones and Merriman (2009) argue that we cannot assume that nationalism is banal for everyone who lives in Britain at the current time, given the complexity of group identities. Skey, and Jones and Merriman advocate for a notion of everyday nationalism, which incorporates banal and mundane processes but may also include a variety of hotter “differences and conflicts” that affect people’s lives on a habitual basis. The notion of everyday nationalism brings into focus the ways in which people make sense of and/or resist nationalisms emanating from the state. For our research, the notion of everyday nationalism suggests two research questions:
- How do individuals, rather than politicians or the media, shape ideas of who can belong to the nation?
- Do micro-blogging platforms enable heightened nationalism and anti-immigrant discourses or do they also provide a platform for challenging such discourses?
Methods:
We purchased all status updates on the social media platform Twitter created between October 1, 2013 and March 1, 2014 containing the words "immigration," "immigrant," "migration", or "migrant," and Bulgaria/Bulgarian, Romania/Romanian, England, UK, or Britain. This five-month period allowed us to examine how the conversation around immigration was shaped by the defining event of the lifting of restrictions on Romanian and Bulgarian migration on 1st January 2014.The sample contains 136,960 tweets.
The first stage of analysis involved quantitative network analysis to explore differences among users with a high degree of network centrality for the months of October and December. Specifically, we analysed all tweets that were in the 90th percentile of influence, which we define here as the 90th percentile of the total number of retweets received per tweet. For a tweet to be in the 90th percentile it needed to receive at least 3 retweets in October and 3.4 retweets in December.
The second stage of this research involved qualitative discourse analysis of a five percent random sample of tweets for the month of October and December. This stage was focused on investigating the migration/immigration discourses embedded in tweets from ‘lone users’ or users that exhibited a low degree of network centrality, and whether, and how, these discourses shifted over time.
Results:
As expected, quantitative analysis reveals that the most influential accounts in each month are typically mainstream media outlets and other leading social media sites. Additionally, the connectedness of these most influential accounts appears to increase over time. Distinct from much research based around "hashtags," however, our focus on related but different key terms produces a sample with a relatively large portion of isolates and very small conversations. Thus, one descriptive finding is that during this period of heightened immigration salience, the ‘conversation’ on Twitter was generally decentralised and not overwhelmingly dominated by any particular actors. In other words, the quantitative analysis suggests that in this instance, Twitter as a micro-blogging platform is not primarily an ‘echo chamber’ and not a highly hierarchical network replicating distributions of media power offline.
The qualitative discourse analysis highlighted the multiplicity of nationalist discourses on immigration that individuals in Britain engaged in towards the end of 2013. The majority of ‘lone users’ were simply tweeting mainstream media headlines or redistributing tweets by the influential Twitter users, without additional commentary. Where it was possible to identify discourses related to immigration from the tweet itself and/or from the user descriptions, a greater proportion of tweets represented an anti-immigration discourse than a pro-immigration discourse. The anti-immigration discourses in both the month of October and December were largely similar, but analysis revealed two key differences: a) In October the focus was on illegal immigrants and immigrant in general, while in December the focus shifted specifically to Romanian and Bulgarian immigrants; b) and there was a palpable moral panic in December about what the lifting of restrictions on January 1st 2014 would mean for immigration to the UK.
Our findings suggest that both those who are anti-immigration and those who are pro-immigration are engaged in the discursive construction of the nation on the micro-blogging platform Twitter. However, the anti-immigrant narratives are much more cohesive, indicating that one organisation sets the tone for anti immigrant discourses. While Twitter provides a platform for challenging this exclusive nationalism, the pro-immigration narratives are too diverse and complex to construct a cohesive discourse that promotes an inclusive idea of the British state and Britishness that can challenge the exclusive nationalism of those promoting an anti-immigration stance.
Future Work:
Future work will involve further quantitative and qualitative analysis to explore change in the structure of the retweet network, and the discourses surrounding migration/immigration over time. Drawing on the terms identified in the qualitative results, additional work will focus on the use of advanced textual analysis methods (such as frequency, ‘co-occurrence’ and ‘co-location’ of terms) for recognising patterns in the use of specific terms in either pro- or anti-immigration tweets. It is our aim that a combination of both automated and manual identification of important terms will further assist in identifying discourses, but also key actors in the propagation of information in tweets surrounding this topic.
References:
Billig, M. (1995) Banal Nationalism. London: SAGE
Skey (2009) ‘The national in everyday life: A critical engagement with Michael Billig’s thesis of Banal Nationalism’. The Sociological Review 57 (2): 331-346.
Jones, R. and P. Merriman (2009) ‘Hot, banal and everyday nationalism: Bilingual road signs in Wales’. Political Geography 28:164-173
Background:
Social media sites such as Facebook played a key role during the so-called ‘Arab Spring’ between December 2010 and March 2011 (Yli-Kaitala, 2014; Khondker, 2011; Hussain & Howard, 2013). While much of the research so far has focused upon Egypt and Tunisia, relatively little is known about the extent to which sites such as Facebook played a role in delivering news and shaping attitudes towards the ‘uprising’ in Libya during this period. This study will explore the perspectives of young Libyans aged between 24 and 35 in relation to the revolution and post-revolutionary period (2011-2016). It does so by presenting an overview of the role of social media in Libyan uprising based on a critical thematic analysis of semi-structured interviews with young Libyans exploring how social media was used to promote dissent and spread information in the country; and a content analysis of a sample of public Facebook pages focusing on the anniversaries of the uprising from 2012 to 2016 to look for changing content at systematic periods.
Objective:
The overall aim of the research is to explore how young Libyans perceive the impact of social media for spreading information and news during the revolutionary and post-revolutionary period 2011-2015
Methods:Firstly, further reading will also be undertaken to keep developing the theoretical framework in this ongoing PhD research. Secondly, fieldwork will be undertaken and empirical data will be collected to answer the research questions. The data is then prepared for the next phase in which it is analysed and evaluated to extract findings and start the write up of the thesis.
References:
Hussain, M. M., & Howard, P. N. (2013). What best explains successful protest cascades? ICTs and the fuzzy causes of the Arab Spring. International Studies Review, 15, 48–66. doi:10.1111/misr.12020
Khondker, H. H. (2011). Role of the New Media in the Arab Spring. Globalizations, 8(5), 675– 679. doi:10.1080/14747731.2011.621287
Yli-Kaitala, K. (2014). Revolution 2.0 in Egypt: Pushing for Change, Foreign Influences on a Popular Revolt. Journal of Political Marketing, 13, 127–151. doi:10.1080/15377857.2014.866412
Background:
Police departments across the United States have started to use social media for investigative purposes. A recent report from the International Association of Chiefs of Police found that 88.7% of law enforcement agencies use social media for criminal investigations (IACP, 2015). As policing extends online, questions arise about how social media content functions as evidence in criminal court proceedings and what leverage it provides in relation to other forms of evidence.
Objective:
This paper uses data from seven New York City gang indictments to analyze how the District Attorney’s (DA) office translates communication on social media (e.g., Facebook messages, Tweets, photos on MySpace) by urban youth into acts of gang conspiracy. The goal of this paper is to highlight the affordances of social media as an operational tool for law enforcement and prosecutors.
Methods:
Indictments in the Criminal Branch of the New York County Supreme Court are typically matters of public record. The seven indictments examined in this paper were collected through the Clerks’ Office or the DA’s office website. Each indictment consists of a series of overt acts - any behavior or action that advances the overall charge of conspiracy. All overt acts were coded by type and content based on the description of the activity in the document.
Results:
Across the seven indictments, the prosecution alleged a total of 1,281 overt acts of gang conspiracy, 617 (or 48%) of which were acts on social media. Our examination of the indictments led to the identification of six distinct ways in which prosecutors use evidence gleaned from social media to define and prosecute New York City youth gangs: 1) Communication on social media is seen as an active behavior that can be attributed to a defendant 2) Social media content allows prosecutors to establish associations between defendants 3) Social media posts allow prosecutors to redefine cases and charges 4) Social media evidence is used to show that defendants self-identify as gang members 5) Social media content (in the form of photos , status updates, and private messages) is used by the prosecution to tie defendants to particular presentations of the self 6) Social media posts function as time-stamped admissions of guilt. The most over-arching prosecutorial affordance was the conflation of saying and doing. This conflation took two forms. First, because communication took place on social media—where it was visible and persistent—prosecutors treated all communication as action. By communicating over social media, the defendants were alleged to have acted in furtherance of a crime. Second, saying was also doing insofar as the prosecutors weighted social media communication as admissions of guilt. Any communication was taken at face value as a statement that one was going to or had done something.
References
International Association of Chief of Police. (2015). 2015 IACP Social Media Survey. [PDF file]. Retrieved from http //www.iacpsocialmedia.org/Resources/Publications.aspx
Background:
The recent increase in the use of the Internet, social media, and surveillance technologies among citizens contributes to redefining the roles of the latter in policing matters. According to some authors, citizens went from being passive consumers of police protection to active public safety co-producers (Bayley and Shearing, 1996; Williamson, 2008). Today, new forms of spontaneous collaboration among citizens in order to solve crimes by using online data and tools have emerged on the Internet (Huey et al., 2013). Researchers in the social sciences and humanities have often conceptualized these citizen initiatives as forms of online vigilantism or "digilantism" (Byrne, 2013). Johnston (1996) defines "vigilantism" as any crime control activities performed by a group of individuals who use or threaten to use force to restore order, and for whom this premeditated and voluntary commitment constitutes an exercise of citizenship. Online vigilantism would rely on a logic of shaming (Williams and Wall, 2007) and revenge (Sharp et al., 2008), and, for some authors, could even constitute a crime comparable to terrorism (Vander Ende, 2014). Yet, these crime-solving practices have seldom been studied empirically (Huey et al., 2013), and few citizens who fight crime online actually identify themselves as vigilantes (Wareham and Chua, 2004). Thus, the relevance of vigilantism used by researchers as a definitional tool to study citizen crime-solving practices should be questioned.
Objective:
To explore whether vigilantism is indeed relevant to the study of citizen crime- solving practices, this research aims to document some of the investigative strategies used by citizens and to understand how these relate to vigilantism.
Methods:
To do so, we studied a Reddit sub-forum entitled Reddit Bureau of Investigation (RBI). With nearly 30,000 members, the RBI’s main objective is to “solve crimes and mysteries”. A non-participant and exploratory observation phase was conducted within 121 discussion threads over a period of two months in 2014 and 2015.
Results:
Our first finding points out that the activities taking place within the RBI have little in common with the vigilante’s characteristics listed above. Indeed, among the investigative strategies that were documented, the use of force, vengeance, and shaming were almost never observed, while often being explicitly condemned. Our second finding points to the frequent mobilization of the "vigilante figure" among RBI members as a rhetorical argument for negative identity construction purposes. While the expressions "not your personal army" and "no witch hunts" were clearly publicized on the RBI homepage, the vigilante figure also transcended investigative and posting practices. Thus, the vigilante figure did not appear relevant as a definitional tool, but rather in its propensity to provide RBI members with a rhetorical object against which they could define who they are (not) and what they do (not).
Future Work:
Rather than applying the vigilante figure in order to define crime solving practices among citizens in a deductive fashion, future research should develop comprehensive models to understand the logic that underlies these specific practices. Future research should also document the collaborative processes on which these online citizen practices rely, as well as how citizens negotiate a criminal investigation ethic through interaction.
References:
Bayley, D. H., & Shearing, C. D. (1996). The future of policing. Law and society review, 585-606.
Byrne, D. N. (2013). 419 Digilantes and the Frontier of Radical Justice Online.Radical History Review, 2013(117), 70-82.
Chua, C. E. H., & Wareham, J. (2004). Fighting internet auction fraud: An assessment and proposal. Computer, 37(10), 31-37.
Huey, L., Nhan, J., & Broll, R. (2012). ‘Uppity civilians’ and ‘cyber-vigilantes’: The role of the general public in policing cyber-crime.Criminology and Criminal Justice, 1748895812448086.
Johnston, L. (1996). What is vigilantism?. British Journal of Criminology, 36(2), 220-236.
Sharp, D., Atherton, S., & Williams, K. (2008). Civilian policing, legitimacy and vigilantism: Findings from three case studies in England and Wales.Policing & Society, 18(3), 245-257.
Wall, D. S., & Williams, M. (2007). Policing diversity in the digital age Maintaining order in virtual communities. Criminology and Criminal Justice,7(4), 391-415.
Williamson, T. (Ed.). (2008). The Handbook of Knowledge Based Policing: Current Conceptions and Future Directions. John Wiley & Sons.
Background:
Several attempts in the academic literature aim at giving a complete overview of Internet-related forms of collective action. The ambition of the present paper is to give a close reading of the repertoire of action of our case study, therefore we consider the use of lists and categories that best fit our focus. Our empirical analysis focuses on Migration Aid, a Hungarian Facebook-based social movement that was established with the aim of providing relief aid for refugees who crossed Hungary in considerable numbers during the summer of 2015. The researched period starts with the group’s inception, 29 June and ends on 15 September – the date when the erection of a fence on the Serbian-Hungarian border and a number of legal changes effectively put an end to the group’s operations in Budapest
Objective: Migration Aid, in the course of a few weeks established a hybrid organization operating both on- and offline, with a wide and highly flexible repertoire of action, without a formal hierarchy or leadership. We argue that this complex undertaking and achievement was mainly made possible by what we coin the Social Information Thermostat function of Facebook. The concept of Social Information Thermostat (SIT) refers to the operation of a self-regulative system which permanently receives inputs from given surroundings and changes its outputs accordingly. At the same time SITs themselves are subjects of continuous change and they drive transformation of the broader context as well.
Methods: The study examined 4616 posts shared in the central, closed Facebook-group of Migration Aid from its inception, 29 June until 15 September, 2015. A combination of close reading and content analysis - also borrowing from Fairclough’s three-dimensional model (2001) of critical discourse analysis (CDA) - were used. The close reading led to the identification of central themes in the group’s posts (see Table 1), where the textual unit of one post was considered a unit of analysis.
Results: Our quantitative findings evidence that during a permanent fluctuation of demands and inputs the group effectively reacts with fitting responses and outputs. We also find that the Facebook-group is central in the establishment, maintenance and connection of diagnostic and prognostic action frames. The long-term co-occurrence of these action frames is also evidenced by the findings. Based on our qualitative analysis we discuss five substantial trends made possible by the Social Information Thermostat function: sophisticated crowd-enabled collaboration, the creation of micromedia, the centrality of mobile communication and location-based networking, and open innovation. Facebook also poses limitations on social movements that are shortly discussed as well.
Future Work: We have finished this paper recently and intend to continue to work on Migration Aid and the refugee crises by exploiting the possibilities provided by different digital footprints than Facebook.
Background:
In the past decade, Europe has witnessed the birth of many rightwing protest movements, such as Pegida and the Identitarian Movement. This interdisciplinary project, jointly conducted by communication scholars and journalists at a leading European daily newspaper, explores the networks and messages that characterize these movements of populist outrage over a period of nine months to better understand their interrelations. It achieves its aim through systematic social media and web data analysis of public communication, combined with expert interviews and onsite research.
Objective:
Our central objective is to map the relations of rightwing movements in Europe with a focus on Germanspeaking countries. Such movements are characterized by their opposition to immigration, European integration, and perceived ‘islamization’. Their organizational structures have commonalities with grassroots civic movements and rely strongly on social media for organization and communication. Since summer 2015, their outrage has had significant impact on public discourse in Europe.
The project’s objectives are summarized by three research questions
Howdonewrightwingmovementscommunicatewitheachotherandtheir followers?
Canconnectionsbeidentifiedbetweenthesemovementsandpoliticalparties?
Howistheearlystagecommunicationofselectedgroupsstructured?Whatare
factors in their communication that let these groups endure?
Methods:
The project takes place over a period of nine months, with successive stages of data collection, analysis, and presentation in different formats. The project combines multiple methods:
Results:
The products of our research will both be disseminated through the mass media and in scholarly publications. These products will take on the form of interactive networks, statistical data, maps and stories. Todate, we have collected:
Future Work:
When the conference takes place, our research will have progressed to an intermediate stage, at which we will be able to present early qualitative (e.g. individual cases) and quantitative (macroscopic relations between actors) results. In addition to the outcome of the project as such, we will also be able to report on the collaboration between academic research and journalism on this vital issue at the interface of public communication and scholarly knowledge.
References:
Borra, E., & Rieder, B. (2014). Programmed method: developing a toolset for capturing
and analyzing tweets. A slib Journal of Information Management, 6 6( 3), 262–278.
Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. P olitical Analysis, 2 1( 3), 267–297. doi:10.1093/pan/mps028
Rogers, R. A. (2013). D igital Methods. Cambridge, MA: MIT Press.
Scharkow, M. (2013). Thematic content analysis using supervised machine learning: An empirical evaluation using German online news. Q uality & Quantity, 4 7( 2), 761–773. doi:10.1007/s1113501195457
Location: PSH (Professor Stuart Hall Building) - LG01,
Goldsmiths, University of London, Building 2
Campus Map
Contributor: Nina Santos, PhD Candidate at Carism/Université Panthéon-Assas
Background:
The biggest protests since the democratization process of Brazil happened in 2013. Millions of citizens went to the streets to fight against the increase of the price of public transportation, but also to demand a higher quality of education and health systems, among other agendas. The FIFA World Cup that took place in the country in 2014 was also a main issue at the time. The lack of protagonism of the traditional social movements that used to mobilize the people to protest was a great issue at the moment. Not only the parties and worker unions were not the one’s organizing the demonstrations, but also the participants had a clear resistance of affiliating with these movements. They preferred a self-organization and anti-political parties discourse. For that, the constant and heavy use of social media was crucial.
In fact, the 2013 protests in Brazil had some of the main characteristics pointed out by authors to explain this new form that the protest movements are taking: the importance of the individual action on the collective action (Bakardjieva, 2015); the role of the technologies of the self on the shaping of collective identities (Cammaerts, 2014); a more personalized form of participation (Bennet et Segerberg, 2012); the use of social media not only as a communication platform, but also as an organizing device (Kavada, 2003).
After that, the wave of protests did not cease. After the tight 2014 Presidential Election, the people occupied the streets again, this time with a different political issue: the impeachment of President Dilma Rousseff. But the issue is far from being unanimous among the Brazilian people so, in fact, two different movements started to organize themselves: one pro and one against the impeachment.
We collected data from Facebook pages of the organizers of two massive protests that happened in December 2015. To identify the main organizers of the protest we searched a number of hashtags used during the mobilization and identified the organizations that posted more about the theme. The mobilization that demands Roussef’s deposition was organized mainly by three very recent movements called: Movimento Brasil Livre – MBL (Free Brazil Movement), Revoltados Online (Online Rebels) and Vem Pra Rua (Come to the Street).
On the other hand, the Roussef’s government has the support of a great deal of traditional social movement and worker’s unions in Brazil. We decided to collect data from de Workers Party page (PT), the page of the Unified Workers Union (CUT) and a new front created on 2015 and called Brazilian Popular Front (Frente Brasil Popular). Although the Frente Brasil Popular is a new political grouping, it is formed by very well-known and ancient Brazilian social movements.
Objective:
The main objective of this article is to discuss the use social media by the recent political street protests in Brazil. Our main questions are: what are the similarities and differences between the use of social media by the pro and against impeachment movements in Brazil? How do they relate and or not to the existing political parties and current elected politicians?
Methods:
We work with data collected from Facebook pages related to the protests of December 2015 to identify the uses of social media made by the organizers of the two protests and the way they relate or not to the political parties and the current elected politicians in Brazil. We do that using the affordances and constraints categories proposed by Cammaerts, 2014.
Results:
We identified that the pro impeachment movement used the social media in a much more intense way than the movement against the impeachment. Also, while the "pro movement" focused on disseminating ideas and mobilizing their supporters, the "against movement" had more posts willing to disseminate ideas and to record their actions. While the movement against the impeachment clearly relates to political parties - even if many of the supporters are not identified with these parties -, the movement pro impeachment declares itself nonpartisan and with no relation to parties. However, we did identify posts that quote elected politicians that supported and helped to convoke the pro-impeachment mobilizations.
Future Work:
This paper is a part of my thesis. My next steps in not only improving the analytical framework by also applying it to a French case of protest to identify similarities and differences.
References:
Bakardjieva, M. (2015). Do clouds have politics? Collective actors in social media land. Information, Communication & Society, (July), 1–8. http://doi.org/10.1080/1369118X.2015.1043320
Bennett, W. L., & Segerberg, A. (2012). The logic of connective action: Digital media and the personalization of contentious politics. Information, Communication & Society, 15(5), 739–768. http://doi.org/10.1080/1369118X.2012.670661
Cammaerts, Bart (2014). Technologies of self-mediation: affordances and constraints of social media for protest movements. In: Uldam, Julie and Vestergaard, Anne, (eds.) Civic engagement and social media - political participation beyond the protest. Palgrave Macmillan, Basingstoke, UK.
Kavada, A. (2003). Social Movements and Current Network Research. ... Social Movement Networks’, Corfu, Greece, 1–21. Retrieved from http://nicomedia.math.upatras.gr/conf/CAWM2003/Papers/Kavada.pdf
References:
Ackland, R. (2013). Web Social Science Concepts, Data and Tools for Social Scientists in the Digital Age (1st ed.). London: SAGE Publications Ltd.
Borge-Holthoefer, J., & Gonzalez-Bailon, S. (2015). Scale, Time, and Activity Patterns: Advanced Methods for the Analysis of Online Networks. In N. Fielding, R. Lee, & G. Blank (Eds.), Handbook of Online Research Methods (Second). Thousand Oaks: Sage Publications. Retrieved from http://ssrn.com/abstract=2686703
Garrett, R. K., & Resnick, P. (2011). Resisting political fragmentation on the Internet. Daedalus, 140(4), 108–120.
Gentzkow, M., & Shapiro, J. M. (2011). Ideological Segregation Online and Offline. The Quarterly Journal of Economics, 126(4), 1799–1839. http://doi.org/10.1093/qje/qjr044
Gitlin, T. (2002). Public sphere or public sphericules? In J. Curran & T. Liebes (Eds.), Media, ritual and identity (p. 168). Routledge.
Gould, R. V, & Fernandez, R. M. (1989). Formal Approach to Brokerage in Transaction Networks. Sociological Methodology, 19, 89–126.
Kleinberg, J. M. (1999). Authoritative sources in a hyperlinked environment. Journal of the ACM (JACM), 46(5), 604–632.
Napoli, P. M. (2008). Toward a model of audience evolution: New Tecnologies and the Transformation of Media Audiences (No. 15). Retrieved from http://fordham.bepress.com/mcgannon_working_papers/15
Newman, M. E. J. (2005). A measure of betweenness centrality based on random walks. Social Networks, 27(1), 39–54.
Newman, N., Levy, D. A., & Nielsen, R. K. (2015). Reuters Institute Digital News. Report 2015. Tracking the future of news. Retrieved from https://reutersinstitute.politics.ox.ac.uk/sites/default/files/Reuters Institute Digital News Report 2015_Full Report.pdf
Pariser, E. (2011). The filter bubble: How the new personalized web is changing what we read and how we think. Penguin.
Prior, M. (2008). Are hyperlinks “weak ties”? In J. Turow & L. Tsui (Eds.), The hyperlinked society: questioning connections in the Digital Age (pp. 227–249). University of Michigan Press Ann Arbor, MI.
Sunstein, C. R. (2009). Republic. com 2.0 (second). Princeton University Press.
Turow, J. (1998). Breaking up America: Advertisers and the new media world. University of Chicago Press.
Webster, J. G., & Ksiazek, T. B. (2012). The Dynamics of Audience Fragmentation: Public Attention in an Age of Digital Media. Journal of Communication, 62(1), 39–56. http://doi.org/10.1111/j.1460-2466.2011.01616.x
Background:
The explosion of social media has changed the ways people communicate and interact. In particular, online communities have enabled people to find the others with common interests, passions, or problems over the Internet, and subsequently to share information, feelings as well give mutual supports. By doing so, online communities can be significantly valuable to the people who use them and hence become a great benefit to society which is regarded as important social capital across multiple dimensions. Despite their increasing value to the society, researchers have noticed that relatively few of them are successful in attracting community members and enhancing interactivity (Phang et al., 2009). To tackle this challenge, we argue that it is necessary to have an in-depth understanding regarding online participation in the communal contexts.
Objective:
From the perspective of online community sustainability, prior researchers have involved investigating the participation roles along with their particular behaviour (e.g. Preece & Schneiderman, 2009) so that their influences in user interactivities in communities can be understood. Whilst these researchers have shed significant light on this domain, the participation patterns pertaining to both the participation roles and the content of message that constantly intertwine in sustaining community activities have received little attention. We argue that in online communities especially those with particular purposes, the content of posts is one of the drivers of user participation in conversations or discussions, and that consequentially leads to different typologies of content networks to emerge (Kane et al., 2014) as well as facilitating networked communication and user interactivities (van Varik & van Oostendorp, 2013).This is important, because people in an online community are not only connected to other people, for they are also connected to the content, which can be connected to other content (Oestricher-Singer & Zalmanson, 2013). This study, by drawing upon the theory of online participation, aims to understand participation patterns consist of roles and content emerged in the community contexts and thereby increasing the value of online knowledge sharing.
Methods:
For this research, a mixed method of social network analysis with both qualitative and quantitative strategies has been undertaken on the discussion forum URcar (a pseudonym). Specifically, the discussion topic about the vehicle model Nissan Cefiro entitled “Cefiro’s owners, please come to sign here” is selected as the main case study (not least) for it being the longest car-related discussion, for the period February 2007 to November 2015 (lasting for nine years and still active) and thus can be considered as an online community with sustainability. The development of this long-lasting discussion topic offers a great opportunity for the study of the users’ dynamic behaviour in a communal context.
Results:
The findings reveal that: first, in online communities with an open conversation space, an individual can participate in a central role in some circumstances, but in a peripheral way in others. Thus, we argue that participation roles are not a signature of the person but a contextual behaviour that has its distinctive social meanings. Second, by exploring the actor-content networks, we found that the “main channels” within which some participants discussed the issues directly related to the car model and the “side channels” within which participants developed their social relationships by talking about something else. In fact, the co-existence of main and side channels led the community being active.
Future Work:
In this research, we redefine the meaning of community contribution. Specifically, through reinterpretation of centrality and de-centrality in networks, we have uncovered the hidden influences which contribute the community in knowledge sharing. That is, by considering the message content as well as the role of offline communication alongside the online form, we have identified some people who have a strong impact on maintaining online community sustainability, despite their lack of posting. In order to reach a rigour level of research, more cases are studied continuously.
References:Kane, G., Alavi, M., Labianca, G. J. and Borgatti, S. P. (2014). What's different about social media networks? A framework and research agenda. MIS Quarterly, 38, 275-304.
Oestricher-Singer, G. and Zalmanson, L. (2013). Content or Community? A Digital Business Strategy for Content Providers in The Social Age. MIS Quarterly, 37, 591-616.
Phang, C. W., Kankanhalli, A. and Sabherwal, R. (2009). Usability and Sociability in Online Communities: A Comparative Study of Knowledge Seeking and Contribution. Journal of the Association for Information Systems, 10, 721-747.
Preece, J. and Schneiderman, B. (2009). The Reader-to-Leader Framework: Motivating Technology-Meditated Social Participation. AIS Transactions on Human-Computer Interaction, 1, 13-32.
van Varik, F. J. M. and van Oostendorp, H. (2013). Enhacning Online Community Activity: Development and validation of the CA framework. Journal of Computer-Mediated Communication, 18, 454-475.
Background:
Much of the existing research into the uses of social media platforms focusses on the exceptional: key moments in politics (e.g. Larsson & Moe, 2014; Sauter & Bruns, 2015, Papacharissi & Blasiola, 2016), sports (e.g. Blaszka et al., 2012; Highfield, 2014), brand management (e.g. Krüger et al., 2012; Nitins & Burgess, 2014), or crisis communication (e.g. Mendoza et al., 2010; Palen et al., 2010; Shaw et al., 2013). For the case of Twitter, because of the way that the Twitter API privileges certain data gathering approaches, such work is usually centred on one or more hashtags or keywords (Burgess & Bruns, 2015). This line of inquiry has produced many useful insights into the uses of Twitter – as documented for example in the collection Hashtag Publics (Rambukkana, 2015) – but arguably it covers only one subset of the various uses of the platform. Routine and everyday social media practices remain comparatively underexamined as a result; for Twitter, therefore, what results is an overrepresentation in the literature of the loudest voices – those users who contribute actively to popular hashtags.
Objective:
This paper presents progress results from a major new study that examines user activity patterns on Twitter well beyond limited hashtag collections, drawing on a comprehensive dataset that tracks the public activities of all Twitter accounts identified by their profile information as Australian. Building on this cohort (currently containing some 2.8 million accounts), we have already mapped the follower/followee relationships within the Australian Twittersphere (Bruns et al., 2014) to identify the clustering patterns that influence – arguably more so than the use of hashtags – how information flows between users. We have also identified the thematic drivers of cluster formation in the network, and have mapped participation in specific Twitter conversations across these clusters.
The paper builds on this earlier work by exploring in depth the day-to-day patterns of activity within the Australian Twittersphere, for a selection of several 24-hour periods during 2015. This provides a unique new insight into how, across an entire national Twittersphere, conversations between users unfold through the day, and documents the extent to which such interactions are guided by existing follower relationships, hashtags, or other contextual markers. Inter alia, our analysis will show which parts of the network are consistently active across all periods, and which are triggered by the events of the day; which are more focussed on publishing new content (through original tweets), on interpersonal conversation (through @mentions), or on news dissemination (through retweets); and which are influential across the network, or remain largely within their own clusters. What is revealed through this work is a largely hidden side of Twitter away from the prominent hashtags.
Methods:
Our comprehensive dataset of the public tweets by some 2.8 million identified Australian accounts enables filtering by the timestamps of tweets. We select several 24-hour periods across 2015 (averaging between 900,000 and 1 million tweets per day), to capture all tweets by Australian users during these days; we then extract from the tweet text any @mentions and retweets of other users, and generate a network map of their interactions to examine the processes of interpersonal engagement between these accounts. In doing so, we determine the properties of this network (and how they change through the course of the day), and examine the extent to which @mention or retweet engagement is a feature of overall activity in the Australian Twittersphere at any one point (that is, to what extent users are simply tweeting undirected personal statements, talk with each other through @mentions, or share other accounts’ posts through retweets). We also correlate this with the network clusters we have already identified in the follower network, to explore whether specific practices (posting, @mentioning, retweeting) are more prevalent in particular clusters of the network.
Results:
The outcomes from this study provide new insights into the dynamics of Twitter engagement well beyond well-understood phenomena such as hashtags. They shed new light on how everyday users utilise Twitter, and document the degree of diversity of the personal networks they actively engage with.
Future Work:
We focus here in the first place on the documentation of comparatively ordinary days in the Australian Twittersphere. Future work will compare such patterns with extraordinary periods (such as major political, media, or sporting events), to explore how and to what extent the routine patterns of Twitter engagement change as breaking news disrupts users’ activities. Additionally, the network analysis presented here will also be combined with automated textual analysis, to examine whether changes in activity patterns through the day are correlated with thematic shifts in the content of the tweets.
References:
Blaszka, M., Burch, L.M., Frederick, E.L., Clavio, G., & Walsh, P. (2012). #WorldSeries: An Empirical Examination of a Twitter Hashtag during a Major Sporting Event. International Journal of Sport Communication, 5(4): 435-453.
Bruns, A., Burgess, J., & Highfield, T. (2014). A “Big Data” Approach to Mapping the Australian Twittersphere. In P.L. Arthur & K. Bode (Eds.), Advancing Digital Humanities: Research, Methods, Theories (pp. 113–129). Houndmills: Palgrave Macmillan.
Burgess, J., & Bruns, A. (2015). Easy Data, Hard Data: The Politics and Pragmatics of Twitter Research after the Computational Turn. In G. Langlois, J. Redden, & G. Elmer (Eds.), Compromised Data: From Social Media to Big Data (pp. 93–111). New York: Bloomsbury Academic.
Highfield, T. (2014). Following the Yellow Jersey: Tweeting the Tour de France. In K. Weller et al., (Eds.), Twitter and Society (pp. 249-262). New York: Peter Lang.
Krüger, N., Stieglitz, S., & Potthoff, T. (2012). Brand Communication in Twitter: A Case Study on Adidas. In PACIS 2012 Proceedings (paper 161). Retrieved from http://aisel.aisnet.org/pacis2012/161.
Larsson, A.O., & Moe, H. (2014). Twitter in Politics and Elections: Insights from Scandinavia. In K. Weller et al., (Eds.), Twitter and Society (pp. 319-330). New York: Peter Lang.
Mendoza, M., Poblete, B., & Castillo, C. (2010). Twitter under Crisis: Can We Trust What We RT? In Proceedings of the First Workshop on Social Media Analytics (SOMA ’10) (pp. 71-79). Retrieved from http://snap.stanford.edu/soma2010/papers/soma2010_11.pdf.
Nitins, T., & Burgess, J. (2014). Twitter, Brands, and User Engagement. In K. Weller et al., (Eds.), Twitter and Society (pp. 293-303). New York: Peter Lang.
Palen, l., Starbird, K., Vieweg, S., & Hughes, A. (2010). Twitter-Based Information Distribution during the 2009 Red River Valley Flood Threat. Bulletin of the American Society for Information Science and Technology, 36(5): 13-17.
Rambukkana, N. (Ed.). (2015). Hashtag Publics: The Power and Politics of Discursive Networks. New York: Peter Lang.
Papacharissi, Z., & Blasiola, S. (2016). Structures of Feeling, Storytelling, and Social Media: The Case of #Egypt. In Bruns et al. (Eds.), The Routledge Companion to Social Media and Politics (pp. 211-222). London: Routledge.
Sauter, T., & Bruns, A. (2015). #auspol: The Hashtag as Community, Event, and Material Object for Engaging with Australian Politics. In N. Rambukkana (Ed.), Hashtag Publics: The Power and Politics of Discursive Networks (pp. 47–60). New York: Peter Lang.
Shaw, F., Burgess, J., Crawford, K., & Bruns, A. (2013). Sharing News, Making Sense, Saying Thanks: Patterns of Talk on Twitter during the Queensland Floods. Australian Journal of Communication, 40(1), 23-39. Retrieved from http://search.informit.com.au/documentSummary;dn=430834117446976;res=IELHSS.
Introduction
The information people choose (in the form of opinions, advice or ideas) determines to a great extent the knowledge they acquire (Barthelme, Ermine, & Rosenthal-Sabroux, 1998; Nonaka, 1994). However, in order to forego the costs of individual learning, people have evolved to acquire knowledge through social learning processes like teaching, language and imitation (Mesoudi, 2011). Specifically, some evolutionary scholars have focused on three biases that take place when grouped individuals interact: they tend to conform to the beliefs of the group (frequency-based); they tend to imitate the ideas of powerful or alike individuals (model-based); or they simply select information that is perceived as having more benefits compared to the other options (content-based), (Mesoudi, 2011; Richerson & Boyd, 2005).
These biases tend to happen whenever people are grouped, but never before have we seen as many individuals interacting as we do now. With almost half of the world’s population making use of the internet (Internet Live Stats, 2015) and given the amount of information that is being shared and received by users, online communities have had to implement different structures that simplify the sharing of information. However, at the same time that these structures simplify and tailor the information we need, they also make us prone to obtaining information that is biased (Kahneman, 2003; Tversky & Kahneman, 1981). These structures affect: the amount of information allowed to be transmitted to other users (maximum or minimum characters allowed per ‘post’), the type of information that can be used (for instance, text, images, or video), the reach within the whole online community (i.e., some opinions are shared only within a selected group of acquaintances while others are meant to be seen by any online user), and the level of conformity towards an idea shared by someone in the network (by making use of different rating-scales).
Objective
The main aim of this research will be to analyse how these different structures might bias the information people receive, and to determine which biases have a greater impact at the moment an individual is choosing from available opinions, advice or ideas. To achieve this, the current research done in social media was structured around the three group-biases (content, model, and frequency-based). The literature review showed that research has already being performed regarding what makes information attractive to others in terms of its content (Cheng & Ho, 2015; Cheung & Thadani, 2012; Jalilvand, Esfahani, & Samiei, 2011; Liu & Park, 2015; Park & Nicolau, 2015), and also in terms of online power or expertise (Iyengar, Van den Bulte, & Valente, 2011; Jacobsen, 2015; Litvin, Goldsmith, & Pan, 2008; Wu, Hofman, Mason, & Watts, 2011). However few studies have addressed the topic of conformity in online networks (Tsao, Hsieh, Shih, & Lin, 2015). Particularly, the differentiation between the personal and the total social network has been under-studied (Jiang, Ma, Shang, & Chau, 2014; Luo & Zhong, 2015). Moreover, although some research has also been performed regarding the comparison of rating-scales in online environments (Riedl, Blohm, Leimeister, & Krcmar, 2010, 2013), these studies have not differentiated personal networks within the online platforms.
Therefore, to address these gaps, the present study explores the following research questions: Which are the biases that mostly affect online choices? How strongly does conformity affect the choices in social media? Do people conform differently to the total-network than to their online personal-networks? Does the selection of information from someone’s personal network get affected by two different rating- systems?
Methods
To target the research questions, the study will adopt a quasi-experimental approach, and the data gathered will be both quantitative and qualitative, and longitudinal in nature. The quasi-experiment will consist of three years of data generated within an online educational website (PeerWise) where the participants will be (non-randomly allocated) undergraduate students of a particular module in the University of Sheffield. This module currently uses PeerWise throughout the semester, where students use it “to create [multiple choice questions] and to explain their understanding of course-related assessment questions and to answer and discuss questions created by their peers" (PeerWise, 2015).
The study will encompass three years of data: [1] The first year will have the characteristic that Peerwise users will be able to choose their usernames1 and rate2 each other’s questions from 0 to 5. [2] In the second year the change that will take place is that anonymity will be removed. This is, all students will be signed-in with their first and last names3, while the rating-scale continue to be 0 to 5. [3] Finally, during the third year students will continue to be logged-in with their first and last names, and the change will be that the rating scale will go from 0-5 to 0-1 (similar to a ‘like/dislike’).
Each year of the quasi-experiment will have 350 students (approx.) which will generate around 54,000 interactions4. This data will be analysed using statistical methods5. Moreover, at the end of each semester students will be asked to complete a questionnaire where their personal networks (within the group) will be mapped. The data from the questionnaire will then be compared with the way users interacted in PeerWise, using social network 6and sequence7 analyses. Finally, yearly focus groups will be used to get additional qualitative data that helps the researcher better understand the opinions and feelings of participants regarding the presence of their personal networks in online environments and the use of a particular rating scale.
Results
Theoretically, this research will add value by addressing the previously outlined research questions. Empirically, the research will create value by performing a real-life quasi-experiment which will enable to study conformity to personal-networks and comparison of online rating-scales with a novel methodology. Regarding practice and policy, it will help to better understand the application of social media to education, by studying which structures better enable students to obtain information and retain knowledge.
Future Work
This study is part of an ongoing Ph.D. At the time of the conference the researcher will be performing the first between-group comparison, and will therefore be able to comment on some of the preliminary results.
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Jacobsen, G. D. (2015). Consumers, experts, and online product evaluations: Evidence from the brewing industry. Journal of Public Economics, 126, 114–123. http://doi.org/10.1016/j.jpubeco.2015.04.005
Jalilvand, M. R., Esfahani, S. S., & Samiei, N. (2011). Electronic word-of-mouth: Challenges and opportunities. Procedia Computer Science, 3, 42–46. http://doi.org/10.1016/j.procs.2010.12.008
Jiang, G., Ma, F., Shang, J., & Chau, P. Y. K. (2014). Evolution of knowledge sharing behavior insocial commerce: An agent-based computational approach. Information Sciences, 278, 250–266.http://doi.org/10.1016/j.ins.2014.03.051
Kahneman, D. (2003). A Perspective on Judgment and Choice: Mapping Bounded Rationality. American Psychologist, 58(9), 697–720. http://doi.org/10.1037/0003-066X.58.9.697
Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29(3), 458–468. http://doi.org/10.1016/j.tourman.2007.05.011
Liu, Z., & Park, S. (2015
...Introduction
Nowadays, much of the public activities and behaviors can be found in social media. Social media became a tool enabling access, delivery, exchange and mobilization of resources embedded in personal networks. Whereas, the impact of such resources on instrumental and expressive actions is well documented in the literature (Lin 2001, Finsveen and van Oorschot 2008), the role of social media in facilitating/blocking different types of resources that may have na impact on the individual's actions remains little studied (Steinfield, Ellison, and Lampe 2008, Ellison et al. 2014). This research focus on the relationship between social media, individual social capital, and patterns of the political participation among Polish citizens.
Theory of social resources
The theory of social resources proposed by Lin (Lin, Vaughn, and Ensel 1981; Lin 1999; Lin 2001) makes explicit the assumption that resources embedded in personal networks have an impact on individual actions and can lead to better socioeconomic status (Lin 1999). He operationalized social capital at the individual level as 'a social asset by virtue of actors’ connections and access to resources in the network or group of which they are members' (Lin 2001). Such resources include symbolic and material goods that make up the social capital (Bourdieu 1986). To distinguish resources owned by others from private resources belonging to an individual, Lin introduced a term 'personal resources'. By personal resources he means “resources possessed by an individual [that] may include ownership of material as well as symbolic goods (e.g., diplomas and degrees)” (Lin 2001).
This research focus on social resources owned by individuals belonging to the respondent's personal network. Based on previous research with the Resource Generator tool (Webber, Huxley, & Harris 2011; Batorski, Bojanowski, & Filipek, 2015), it is assumed here that only some resources could be mobilized in a purposive action. In other words, relatives, friends and acquaintances may possess certain resources, but individuals are not able to use them when acting in various social contexts.
Thus, the main goal of this research is to find out whether and how resources embedded in personal networks (family, friends, acquaintances) influence the political participation of social media users. The following research questions are pursued:
- Do embedded and/or mobilizable resources in personal networks affect the political participiation of respondents?
- What is the impact of resources on respondents' activities selected in this research as indicators of the political participation?
- Whose resources, namely family, friends, acquaintances or respondents have an impact (positive or negative) on the political participation?
Methods:
The core of the measuring tool is based on the Resource Generator (RG) (Van Der Gaag and Snijders 2005). Items included in the RG are the major independent variables. The RG items refer to the four types of resources (i.e. support, knowledge, recommendation, and material resources) embedded and mobilized through personal networks, that may have an impact on the individual's participation.
The dependent variable is represented by five items (5-point Likert scales) reflecting the respondents' political participation. Those items include (1) voting in elections, (2) signing petitions, (3) joining protests, (4) personal contacts with politicians, (5) local community meetings.
The data has been collected through the online questionnaire among individuals registered at the online research platform delivered by external partner. The research has been conducted in December 2015 on stratified random sample of 1000 (700 SM users and 300 non-users) residents of Poland.
Results:
The research shows that resources embedded in family, friends and acquaintances ties have an impact on the political participation of respondents. The impact of resources appears be either positive or negative depending on the activity selected for analysis. For example, resources that could be only accessed, but not mobilised by respondents have no impact on dependent variable defined as voting in elections. At the same time, resources that could be mobilized have positive impact on voting. When signing petition activity is examined the impact of resources is reversed. There is no effect of mobilizable resources and positive impact of resources that are embedded in individual's personal network. The strong ties (family and friends) are better source of embedded resources that have a positive impact on the political participation of social media users in Poland. In general, weak ties have no or negative effect on activities examined in this research. The only exception is voting in elections. It is found that resources mobilizable through weak ties may have a positive impact on respondents voting activity.
Thus, the amount and quality of social capital embedded in personal networks matter when the political participation is considered. Resources embedded in family, friends and acquaintances circles have an impact on certain activities exemplifying the political participation of social media users in Poland.
Future Work:
The quantitative data will be combined with the qualitative data obtained via in-depth interviews based on position generator tool.
References:
Batorski, D., Bojanowski, M., & Filipek, K. (2015). Getting a Job: Resources and Individual’s Chances on the Warsaw Labour Market. Polish Sociological Review, 192(4).
Bourdieu, P. (1986). The Forms of Capital. In J. G. Richardson (Ed.), Handbook of Theory of Research for the Sociology of Education (pp. 46–58). New York: Greenwood Press.
Ellison, N. B., Vitak, J., Gray, R., & Lampe, C. (2014). Cultivating Social Resources on Social Network Sites: Facebook Relationship Maintenance Behaviors and Their Role in Social Capital Processes. Journal of Computer-Mediated Communication, 19(4), 855–870. http://doi.org/10.1111/jcc4.12078
Finsveen, E., & van Oorschot, W. (2008). Access to Resources in Networks: A Theoretical and Empirical Critique of Networks as a Proxy for Social Capital. Acta Sociologica, 51(4), 293–307. http://doi.org/10.1177/0001699308097375
Lin, Nan. 1999. “Building a Network Theory of Social Capital” edited by N. Lin, K. S. Cook, and R. S. Burt. Connections 22(1):28–51.
Lin, Nan. 2001. Social Capital. A Theory of Social Structure and Action. Cambridge University Press.
Lin, Nan, John C. Vaughn, and Walter M. Ensel. 1981. “Social Resources and Occupational Status Attainment *.” Social Forces 59(4):1163–81. Retrieved (social resources, netoworks).
Steinfield, C., Ellison, N. B., & Lampe, C. (2008). Social capital, self-esteem, and use of online social network sites: A longitudinal analysis. Journal of Applied Developmental Psychology, 29(6), 434–445. http://doi.org/10.1016/j.appdev.2008.07.002
Van Der Gaag, M., & Snijders, T. a. B. (2005). The Resource Generator: social capital quantification with concrete items. Social Networks, 27(1), 1–29. http://doi.org/10.1016/j.socnet.2004.10.001
Webber, M., Huxley, P., & Harris, T. (2011). Social capital and the course of depression: Six-month prospective cohort study. Journal of Affective Disorders, 129(1-3), 149–157. http://doi.org/10.1016/j.jad.2010.08.005
Background:
How is consensus found in small groups that negotiate important Internet protocols, just using public email listservers? This project analyses three important threads on a public email listserver that contain the email exchanges of a small group of people who were chartered by the IETF with updating our current HTTP protocol, that underlies all our traffic on the Internet. It was an update that was long overdue, and is still in the wake of being finalized. The Internet Engineering Task Force (IETF) is an international Internet standard setting organisation. In general, its mandate is to identify and develop technical standards for the entire Internet, anywhere in the world. It is one of the most unregulated, independent, transnational, and anti-authoritarian Internet governance levels. Given the considerable number of users affected by these standards, vested interests emerge and are vigorously pursued, at times. Only a very small number of studies have shed light on the socio-economic and political role of this organisation, exploring how the IETF works, who benefits from their procedures and publications, and how much deference is paid to corporate interests that claim patents or intellectual property rights.
The selected email threads contain discussions on the required changes to make the next generation HTTP a success. One particularly contested point was how much of the world’s next HTTP should be based on Google’s SPDY (read ‘speedy’), developed by Mike Belshe and Robert Peon while they were employed by Google (both have since left). SPDY was launched by Google in 2009 without IETF standardisation, and included some business enhancing possibilities for their social media platforms (see https://tools.ietf.org/html/draft-mbelshe-httpbis-spdy-00). Their corporate search and social media business model is straightforward. While people are engaged in entering searches or exchanging their views and opinions online automatically all their online entries and machine data are tracked, stored, analysed, bought and sold without public oversight (Hoofnagle & Whittington 2014). Although the possibility for online exchanges is usually viewed positively, online users are divided over the merits of the corporate use of their personal data (PEW 2015, Goodman 2006, Peacock under review).
Additionally, pervasive monitoring (PM) with its continuous analysis of web traffic by governmental agencies was identified as a problem that needed attention in any HTTP update: “Pervasive monitoring is a technical attack that should be mitigated in the design of IETF protocols, where possible” (Farrell & Tschofenig 2014, p. 1). In the wake of this development, the HTTP working group who was chartered with the design of the new HTTP framed PM as relevant to their work. These and other discussions lead to increased their independence from the initial corporate push to merely standardise SPDY.
Objective:
In international organisations people selectively share important knowledge to strengthen in-group coherence, enhancing social status of some while producing social exclusion of others. The current study offers evidence of the social tension between corporate interests and the public goods character of the Internet. Given the salience of the HTTP/2 charter corporate actors, online agency and user advocacy feature prominently in select online discussions.
The current work is not so much about the merits of our new HTTP/2 but focuses on the way rough consensus in this working group is produced using tools of social media. The extent of rough consensus is at the very heart of this project and the use of social media – in this case, an early form of social media, namely public email listservers – serves as my empirical case study. According to an earlier study by Froomkin (2003) discussion in IETF working groups are an ideal case of an inclusive practical discourse that Habermas seems to have envisioned as a public sphere (Habermas 1989, Froomkin 2003). The questions answered in this study are twofold: When does rough consensus succeed or fail and who are the most central people in this process? Furthermore, in how far do online discussions emulate an inclusive practical discourse, particularly if the politics of engineering Internet standards for the entire world is at the heart of the discourse?
As one of the first institutional bodies of standardising best practise on the Internet, a dated but proven email listserver tool is used to exchange ideas and opinions. In the current high-stakes case to produce the next generation HTTP, I assess behavioural objectives and social interactions amongst the working group (WG) members who are all volunteers, vis-à-vis dominant corporate agents to analyse how consensus is build or fails to be build. Most email inputs in the archive contain technical specifications or experiments (testing applications in the wild), but the launch of the charter to construct a new HTTP/2 saw deeply social topics covered like the degree of independence of the IETF which shows the political nature of Internet engineering. In the end, what is made possible or inhibited by technology are very often political decisions made by a small number of people which then go on to affect a large number of people, in this case the entire world (if adoption is successful).
Of particular interest are the initial three months when the group’s charter is discussed. Members weigh into the merits of SPDY versus a more secure HTTP, and debate the extent of their options to have more independence. Given the corporate presence of WG members with heavy ties to Google, Mozilla and a number of other large Internet firms and an already existing ‘new’ HTTP (SPDY) members felt heavily nudged towards ‘rubberstamping’ corporate online interests. But other opinion leaders emerged to insist on broadening their assignment. Eventually, this lead to a more consensual move: SPDY was used as a mere backdrop and while the group independently improved the current HTTP. A small number of people dominated the discourse resulting in the outcome we have today – an improved HTTP with backward compatibility and better options to circumvent PM. According to Haberman, this can be viewed as an outcome of delegation when important decisions are delegated to people who are considered more capable than others. As might be expected, a considerable number of emails focused on the very nature of the WG’s assignment and the envisioned end product, given the urgent need for more thorough HTTP updates. Humour, allcaps, hilarity, and rhetoric are used as members engage in highly contentious exchanges, which is usually a good indication of the political nature of their work. Taken together, a theoretical framework of the public sphere seems appropriate to advance my analysis of the empirical data produced by this working group.
Methods:
My research includes the representation of knowledge, rules, clout, and classifications in the publicly accessible email contributions from working group members (WG). These public contributions are of a very peculiarly nature, because public access to the email list is obscure while at the same time, full public access is granted, if anyone finds them. Currently, I am finishing the analysis of emailed contributions from members of the HTTP/2 WG on the contentious discussions about the extent of their charter and questions surrounding the inclusion of Google’s SPDY for the new HTTP/2. To wit, SPDY had been in use since 2009, and the number of company heads who were adopting it without IETF standardisation was increasing (e.g., Amazon in September 2009 or Netty in February 2012). Discussions on how to recharter the HTTP/2 working group started in January 2012. The first http proposal was officially launched in February 2012 (based fully on SPDY). In the next two months at three different discussion threads ensued containing lively debates on the question how much of our next generation HTTP should be based on Google’s SPDY.
The choice of this case study is based on its importance for the online public sphere, particularly regarding user agency and the fact that social media were used to negotiate technical choices. Contentious issues are identified by the comments of group members and in published articles outside the WG that describe this particular piece of engineered standard setting (e.g., Kristol 2001, Kamp 2015). The full list of email discussions on the HTTP/2 standard is hosted by the IETF HTTP WG (see http://httpwg.github.io/). Additionally, an IETF meeting took place in Paris in March 2012 (IETF 83) that offers some insights of how the discussion of the charter continued face-to-face. All of these materials are publicly accessible, although members expect little public scrutiny beyond those immediately contributing and involved in the discussions. Therefore the archives are characterised as quasi-public in my current work.
The contex
...Background:
This study was prompted by discussion among the authors about activity in the discipline of Emergency Medicine(EM), whereby practitioners and academic researchers were actively using social media to communicate with each other and in particular for transmitting information about the latest practices in patient treatment - highlighted by an active online community (FOAMeD) (Life in the Fast Lane, n.d.) and an annual conference (SMACC) – Social Media and Critical Care. These processes provide a dynamic and cost-free platform for communicating between academia and clinical practice (Scott, et al., 2014), for which serious benchmarking has been recommended by EM practitioners (Weingart & Faust, 2014). By contrast the multitude of conferences in the Information Technology/ Computer Science (IT/CS) space have had a tendency to polarize discussion into either academic or industry streams, with less social media engagement. This project is to explore the SM engagement between two technology focused disciplines.
Objective:
To identify how different the social media engagement is between EM & IT/CS, and to analyse the reasons for such differences.
Methods:
The public websites of all Australian publicly funded universities were examined to locate the names of professorial staff in IT or Computer Science schools, and academic staff in Emergency Medicine disciplines in Medical schools. The latter were harder to locate as not all medical school websites listed staff in discipline groups, resulting in 3 times the number of identified IT vs EM staff examined. But in both discipline areas any names found were then used to explore for a Twitter account. The names were then used to search for accounts on twitter and where the biographical data did not indicate a direct match – the people being followed and the pubic tweets were examined to try to confirm a link to indicate a match to the institution or relevant discipline topics. It is possible that some of the examined identities were using a false identity on Twitter but it was assumed that total anonymity did not indicate an engagement with Twitter as part of the subject’s professional activity. Whilst the existence of related Facebook accounts was examined for IT/CS staff, the privacy settings and closed nature of Facebook make it less accessible for study. Twitter was also considered more generally the platform for open professional discussions.
Results:
Table 1. Comparison of Twitter Activity
In addition to examining Twitter involvement, for the IT/CS cohort, they were searched for on Facebook and 41 (or 22%) were found with public accounts.
The median results were included as the means in each case were raised in both disciplines by a small number of very active individuals.
Future Work:
The initial results above reinforced the impression that IT/CS academics whilst supposedly heavily engaged with technology have shown a reluctance as a discipline to engage with social media driven by the platforms for which they are experts. During the examination of the Tweets of the accounts it was noted that there seemed a trend in the IT/CS tweets to be more public notices then a real engagement or discussion that was shown in the EM activity. The next step is to survey academics in the two disciplines to identify the details of their use of SM and to use frameworks such as in (Ngai, Tao, & Moon, 2014) to analyse the respective engagement. This could also include more systematic analysis of the content of the Tweets.
References:
(n.d.). Retrieved January 12/1/2016, 2016, from Life in the Fast Lane: http://lifeinthefastlane.com/foam/
Ngai, E., Tao, S., & Moon, K. (2014, October 19). Social media research: Theories, constructs, and conceptual frameworks. International Journal of Information Management, 35, 33-44.
Scott, K., Hsu, C., Johnson, N., Mamtani, M., Conion, L., & DeRoos, F. (2014, October). Integration of Social Media in Emergency Medicine Residency Curriculum. Annals of Emergency Medicine, 64(4), 396-404.
Weingart, S., & Faust, J. (2014). Future evolution of traditional journals and social media medical education . Emergency Medicine Australia, 26, 62-66.
Background:
Haythornthwaite and Wellman’s seminal work establishing the importance of multiplexity in social contacts across various communication media established from an early point that accounting for the various networks individuals interact upon is of primary importance. This work addresses a methodological concern with studies on multiplexity - specifically, this work imagines trials of synthetic multilayer networks where ties made across layers are potentially incorrect in several ways. The work then examines the effect of these incorrect ties in terms of how analyzing the diffusion of a rumor may differ from cases where all ties are correctly assigned.
Objective:
This paper aims to contribute to methodological practices around measuring multilayer networks in emergent situations, such as a breaking news event of an online activist campaign. The issue at hand is largely concerned with failures to correctly identify cross ties between network layers, and how various failures result in different outcomes than an identical counter-factual case where those failures are not present.
Methods:
The work employs a network modeling approach combined with a rumor diffusion model. The paper establishes several parameters of interest that approximate different types of failures in generating ties between two networks, and then modulates those parameters randomly over many stochastic realizations of the model, while always having two control cases with the same parameters for each realization to allow for a comparison between what is different in a case where failures occur. From this, a comparison one zero failure (where ties across networks are perfectly set) case against the other zero failure case and one zero failure case and the failure case (where ties across networks are imperfectly set) allows for a close examination of the impact of these failures on being able to correctly measure outcomes from the network.
Results:
The results indicate that only certain types of errors actually damage downstream analysis of emergent events in multilayer networks. Specifically, as long as the approximate number of cross ties is close to the correct amount, even if those ties are misclassified, the results will mostly allow for a close analysis that is correct in its findings. If, however, many ties fail in the sense that those links between the networks are never drawn, the results will deviate from the control case.
Background:
The gender gap in science has been subject of many recent discussions and analyses. Female authors have been shown to be less productive and have less impact as reflected in the number of papers and citations (Larivière, Ni, Gingras, Cronin, & Sugimoto, 2013). However, the landscape of research dissemination and impact is changing, with the adoption of social media by scholars and the use of “altmetrics” in research evaluation. It therefore begs the question on the extent to which this new environment replicates the gender disparities observed in the old (Paul-Hus, Sugimoto, Haustein, & Larivière, 2015). Internet technologies are promoted for their ability to democratize and flatten traditional hierarchies and women indeed show a slightly higher level of participation on social networking sites (Perrin, 2015). This suggests that measures of visibility based on social media may achieve greater gender parity than citation-based impact measures.
Objective:
Based on the social media activity of 769,695 journal articles covered by the Web of Science (WoS), this study aims to compare the amount of attention papers first-authored by male and female researchers receive via Mendeley, Facebook, Twitter, blogs and Wikipedia and to analyze any potential differences by platform and discipline.
Methods:
Gender was determined for the first authors of 769,695 articles and reviews published in 2013 in journals covered by WoS using the method developed by Larivière et al. (2013). For each of these papers, the number of unique Twitter users, public Facebook posts, blog posts, and Wikipedia entries were obtained from Altmetric.com and the number of readership counts retrieved via the Mendeley API using DOIs. Social media events were matched to the bibliographic and citation information from WoS and analyzed by gender and discipline. Results were compared using density, coverage, and 99th percentiles of particular events (Haustein, Costas, & Larivière, 2015). Stability intervals based on 95% confidence intervals of bootstraps (1,000 replications with replacement) were computed for each indicator to test the significance of gender differences.
Results:
The number of papers led by female (n=269,054) compared to male first authors (n=500,641) replicates the well-established gender gap. Scientific impact reflects the same pattern, as relative citation rates of papers with male exceed those of papers with female first authors in all disciplines. The results for social media visibility differ by social media platform, discipline, and indicator. Based on coverage–i.e., the percentage of papers with at least one social media event—most differences between female and male papers are small and not significant (Figure 1). Among significant results, male papers are more likely to be cited on Wikipedia or blogs, while Mendeley tends to show higher coverage for papers first-authored by women. Twitter and Facebook coverage varies according to discipline.
Future Work:
As social media events per paper are extremely skewed and results differed between coverage, density, and 99th percentile, future work involves a more detailed analysis of the particular distributions using percentile ranks.
References:
Haustein, S., Costas, R., & Larivière, V. (2015). Characterizing social media metrics of scholarly papers: The effect of document properties and collaboration patterns. PLoS ONE, 10(3), e0120495. http://doi.org/10.1371/journal.pone.0120495
Larivière, V., Ni, C. C., Gingras, Y., Cronin, B., & Sugimoto, C. R. (2013). Global gender disparities in science. Nature, 504(7479), 211–213.
Paul-Hus, A., Sugimoto, C. R., Haustein, S., & Larivière, V. (2015). Is there a gender gap in social media metrics? (pp. 37–45). Presented at the 15th International Conference on Scientometrics and Informetrics, Istanbul, Turkey. Retrieved from http://www.issi2015.org/files/downloads/all-papers/0037.pdf
Perrin, A. (2015). Social Networking Usage: 2005-2015. Pew Research Center. Retrieved from http://www.pewinternet.org/2015/10/08/2015/Social-Networking-Usage-2005-2015/
Background:
Media scholars have systematically examined the implications of social media on society. The ways the same technology adopt into organizations is a more uncertain area of knowledge in organization studies. This aspect relates to that organization theorists prefer to engage into theorizing, than putting focus on how social media is actually used among people in organizational life. This leads to an emphasis on explaining what social media “is”, than painting a larger picture on how receptive organizations are to adopt the forces of digitalization.
Objective:
Hence, the paper provides a research review of a large sample of empirical studies, which have examined how members in organizations use three social media services – blog, Social Network Sites and wikis. Based on an open coding strategy, the research review tries to establish common user patterns for use of social media in organizational life.
Methods:
To complete the research review, an open-ended literature research search was performed in bibliographic databases by use of search strings. The search and data analysis period lasted from January to May 2015 and yielded a final data sample of 105 research articles, covering scientific journals and conference papers evaluated to answer the paper’s problem complex.
Results:
The research review finds some overall user patterns for use of social media in organizations. Social media services are foremost used as a connecting site and knowledge repository. Here, wikis suggest to work as a successful knowledge repository. Employees use social media services to search and retrieve resources and communicate with people across internal organizational boundaries. For example, blogs and SNSs can enhance internal communication in organizations. But many studies also show barriers to adoption; blog and SNSs are often sustained by a core group and sharing is seen as challenging to perform in practice. SNSs are however seen as a platform that can cultivate social capital across organizational levels. To communicate externally, SNSs are typically used as a bulletin board, while employees are conscious on how they bond with peers internally in organizations. Wikis are often used as a collaborative tool and can be a suitable platform to support work processes, meaning that users are aware on their role performance.
In sum, the research review suggests that organizations attempt to ascertain basic knowledge on initial user patterns. Few studies report changes in organizational structures. Thus, social media has challenges in becoming sustainable. Rather, adopting social media in organizational life is an “uphill struggle” for those seeing it as beneficial. For many employees, social media represents another ICT that has to be learned. Therefore, one finds the common user pattern that a core group of users adopt the technology and maintain network activities, while a larger user group remain and use “older” ICTs. They remain in the email sphere and passively monitor the online content the core group shares.
Future Work:
The research review will give suggestions for areas of future research and how practitioners and managers can use social media as part of their work practices.
References:
Scholz, T. (2015, April 5) Think Outside the Boss. Public Seminar. Retrieved from http://www.publicseminar.org/2015/04/think-outside-the-boss
