Publication Type
Journal Article
Version
publishedVersion
Publication Date
9-2014
Abstract
One might think that, compared to traditional media, social media sites allow people to choose more freely what to read and what to share, especially for politically oriented news. However, reading and sharing habits originate from deeply ingrained behaviors that might be hard to change. To test the extent to which this is true, we propose a Political News Sharing (PoNS) model that holistically captures four key aspects of social psychology: gratification, selective exposure, socialization, and trust & intimacy. Using real instances of political news sharing in Twitter, we study the predictive power of these features. As one might expect, news sharing heavily depends on what one likes and agrees with (selective exposure). Interestingly, it also depends on the credibility of a news source, i.e., whether the source is a social media friend or a news outlet (trust & intimacy) as well as on the informativeness or the enjoyment of the news article (gratification). Finally, a Twitter user tends to share articles matching his own political leaning but, at times, the user also shares politically opposing articles, if those match the leaning of his followers (socialization). Based on our PoNS model, we build a prototype of a news sharing application that promotes serendipitous political readings along our four dimensions.
Keywords
News sharing, Political News, Political diversity, Social media, Twitter
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media
Research Areas
Data Science and Engineering
Publication
EPJ Data Science
Volume
3
Issue
1
First Page
1
Last Page
21
ISSN
2193-1127
Identifier
10.1140/epjds/s13688-014-0012-2
Publisher
SpringerOpen
Citation
AN, Jisun; QUERCIA, Daniele; CHA, Meeyoung; GUMMADI, Krishna; and CROWCROFT, Jon.
Sharing political news: the balancing act of intimacy and socialization in selective exposure. (2014). EPJ Data Science. 3, (1), 1-21.
Available at: https://ink.library.smu.edu.sg/sis_research/6286
Copyright Owner and License
Authors-CC-BY
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.1140/epjds/s13688-014-0012-2
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons, Social Media Commons