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Session 4A [clear filter]
Wednesday, July 13
 

10:45

Session 4A: Privacy: Disclosure, Risk & Benefit
Location: PSH (Professor Stuart Hall Building) - LG02, 
Goldsmiths, University of London, Building 2
Campus Map 

Moderators
Wednesday July 13, 2016 10:45 - 12:15
PSH (Professor Stuart Hall Building) - LG02 Goldsmiths University, Building 2

10:46

Commercial Social Media and the Academic Library: A Critical Examination of the Impact on Patron Privacy
Location: PSH (Professor Stuart Hall Building) - LG02, 
Goldsmiths, University of London, Building 2
Campus Map 

Contributor: Jeff Lilburn, Mount Allison University, Canada

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.



Wednesday July 13, 2016 10:46 - 12:15
PSH (Professor Stuart Hall Building) - LG02 Goldsmiths University, Building 2

10:46

Rethinking Social Media Information Disclosure: An Application of Users and Gratifications Theory
Location: PSH (Professor Stuart Hall Building) - LG02, 
Goldsmiths, University of London, Building 2
Campus Map 

Contributors:
  • Kathryn Waite,Heriot Watt University
  • Gary Hunter, Illinois State University
  • Ian Grant, Strathclyde University

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.


Wednesday July 13, 2016 10:46 - 12:15
PSH (Professor Stuart Hall Building) - LG02 Goldsmiths University, Building 2

10:46

Watching me watching you: How observational learning affect self-disclosure on SNS
Location: PSH (Professor Stuart Hall Building) - LG02, 
Goldsmiths, University of London, Building 2
Campus Map 

Contributors:
  • Tamar Ashuri, Department of Communication, Tel Aviv University, Israel
  • Shira Dvir Gvirsman, Department of Communication, Tel Aviv University, Israel
  • Ruth Halperin, Oranim College of Education, Israel

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.

Wednesday July 13, 2016 10:46 - 12:15
PSH (Professor Stuart Hall Building) - LG02 Goldsmiths University, Building 2

10:46

“What Is It And How Did It Get Here?” Factors Related To Advertising Place And The Use Of Personal Data Influencing User Acceptance Of Facebook Ads
Location: PSH (Professor Stuart Hall Building) - LG02, 
Goldsmiths, University of London, Building 2
Campus Map 

Contributors:
  • Evert Van den Broeck, University of Antwerp, Belgium
  • Karolien Poels, University of Antwerp, Belgium
  • Michel Walrave, University of Antwerp, Belgium

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


Wednesday July 13, 2016 10:46 - 12:15
PSH (Professor Stuart Hall Building) - LG02 Goldsmiths University, Building 2