Sharing political news: The balancing act of intimacy and socialization in selective exposure

Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft

Research output: Contribution to journalArticle

26 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1-21
Number of pages21
JournalEPJ Data Science
Volume3
Issue number1
DOIs
Publication statusPublished - 2014

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Keywords

  • News sharing
  • Political diversity
  • Political news
  • Social media
  • Twitter

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Mathematics
  • Modelling and Simulation

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