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Session 2D [clear filter]
Tuesday, July 12
 

13:30

Session 2D: Social Media Access & Use
Location: PSH (Professor Stuart Hall Building) - LG01, 
Goldsmiths, University of London, Building 2
Campus Map 


Moderators
avatar for Jenna Jacobson

Jenna Jacobson

Assistant Professor, Ryerson University
@jacobsonjenna

Tuesday July 12, 2016 13:30 - 14:30
PSH (Professor Stuart Hall Building) - LG01 Goldsmiths University, Building 2

13:31

An Exploration of the Uses and Gratifications (U&G) of Twitter and its Features
Location: PSH (Professor Stuart Hall Building) - LG01, 
Goldsmiths, University of London, Building 2
Campus Map 

Contributors:
  • Anabel Quan-Haaseand, University of Western Ontario, Canada
  • Lori McCay-Peet, Dalhousie University, Canada

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 


Tuesday July 12, 2016 13:31 - 14:30
PSH (Professor Stuart Hall Building) - LG01 Goldsmiths University, Building 2

13:31

Examining the Moderating Role of Personality Traits in the Effect of Microblogging Usage on Social Capital
Location: PSH (Professor Stuart Hall Building) - LG01, 
Goldsmiths, University of London, Building 2
Campus Map 

Contributor: Yu Guo, Macau University of Science and Technology, China

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.


Tuesday July 12, 2016 13:31 - 14:30
PSH (Professor Stuart Hall Building) - LG01 Goldsmiths University, Building 2

13:31

The Social Structuration of Six Major Social Media Platforms in the United Kingdom: Facebook, LinkedIn, Twitter, Instagram, Google+ and Pinterest
Location: PSH (Professor Stuart Hall Building) - LG01, 
Goldsmiths, University of London, Building 2
Campus Map 

Contributors:
  • Grant Blank, Oxford Internet Institute, United Kingdom
  • Christoph Lutz, BI Norwegian Business School, Norway

Sociological studies on the Internet have often examined digital inequalities. These studies show how Internet access, skills, uses and outcomes vary between different population segments. However, we know more about social inequalities in general Internet use than in social media use. Especially, we lack differentiated statistical evidence of the social profiles of distinct social media platforms. To address this issue, we use a large survey data set in the United Kingdom and investigate the social structuration of six major social media platforms. We find that age and socio-economic status are driving forces of several – but not all – of these platforms. Aggregating platform adoption into a general measure of social media use blurs some of the subtleties of more fine-grained indicators, namely platform uses and specific activities, such as status updating and commenting. 

Tuesday July 12, 2016 13:31 - 14:30
PSH (Professor Stuart Hall Building) - LG01 Goldsmiths University, Building 2