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News We Like to Share : How News Sharing on Social Networks Influences Voting Outcomes

Author

Listed:
  • Pogorelskiy. Kirill

    (University of Warwick)

  • Shum, Matthew

    (Caltech)

Abstract

More voters than ever get political news from their friends on social media platforms. Is this bad for democracy? Using context-neutral laboratory experiments, we find that biased (mis)information shared on social networks affects the quality of collective decisions relatively more than does segregation by political preferences on social media. Two features of subject behavior underlie this finding : 1) they share news signals selectively, revealing signals favorable to their candidates more often than unfavorable signals ; 2) they naıvely take signals at face value and account for neither the selection in the shared signals nor the differential informativeness of news signals across different sources.

Suggested Citation

  • Pogorelskiy. Kirill & Shum, Matthew, 2019. "News We Like to Share : How News Sharing on Social Networks Influences Voting Outcomes," The Warwick Economics Research Paper Series (TWERPS) 1199, University of Warwick, Department of Economics.
    • Handle: RePEc:wrk:warwec:1199
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    References listed on IDEAS

    as
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    Cited by:

    1. Battaglini, Marco & Morton, Rebecca & Patacchini, Eleonora, 2020. "Social Groups and the Effectiveness of Protests," CEPR Discussion Papers 14385, C.E.P.R. Discussion Papers.
    2. Buechel, Berno & Mechtenberg, Lydia, 2019. "The swing voter's curse in social networks," Games and Economic Behavior, Elsevier, vol. 118(C), pages 241-268.
    3. Boris Ginzburg, 2023. "Slacktivism," Journal of Theoretical Politics, , vol. 35(2), pages 126-143, April.
    4. Dugar, Subhasish & Shahriar, Quazi, 2023. "Lying for votes," Games and Economic Behavior, Elsevier, vol. 142(C), pages 46-72.
    5. Ayesha Ali & Ihsan Ayyub Qazi, 2021. "Countering Misinformation on Social Media Through Educational Interventions: Evidence from a Randomized Experiment in Pakistan," Papers 2107.02775, arXiv.org.
    6. Felix Chopra & Ingar K. Haaland & Christopher Roth, 2019. "Do People Value More Informative News?," CESifo Working Paper Series 8026, CESifo.
    7. van Gils, Freek & Müller, Wieland & Prüfer, Jens, 2020. "Big Data and Democracy," Other publications TiSEM ecc11d8d-1478-4dd2-b570-4, Tilburg University, School of Economics and Management.
    8. Ali, Ayesha & Qazi, Ihsan Ayyub, 2023. "Countering misinformation on social media through educational interventions: Evidence from a randomized experiment in Pakistan," Journal of Development Economics, Elsevier, vol. 163(C).
    9. Joan Calzada & Nestor Duch-Brown & Ricard Gil, 2021. "Do search engines increase concentration in media markets?," UB School of Economics Working Papers 2021/415, University of Barcelona School of Economics.
    10. Jacob Meyer & Prithvijit Mukherjee & Lucas Rentschler, 2024. "Moderating (mis)information," Public Choice, Springer, vol. 199(1), pages 159-186, April.
    11. Garz, Marcel & Sörensen, Jil & Stone, Daniel F., 2020. "Partisan selective engagement: Evidence from Facebook," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 91-108.
    12. Budzinski, Oliver & Gänßle, Sophia & Lindstädt-Dreusicke, Nadine, 2021. "Data (r)evolution - The economics of algorithmic search and recommender services," Ilmenau Economics Discussion Papers 148, Ilmenau University of Technology, Institute of Economics.
    13. Giacomo De Luca & Thilo R. Huning & Paulo Santos Monteiro, 2021. "Britain has had enough of experts? Social networks and the Brexit referendum," Discussion Papers 21/01, Department of Economics, University of York.
    14. Bowen, T. Renee & Galperti, Simone & Dmitriev, Danil, 2021. "Learning from Shared News: When Abundant Information Leads to Belief Polarization," CEPR Discussion Papers 15789, C.E.P.R. Discussion Papers.

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    More about this item

    Keywords

    news sharing ; social networks ; voting ; media bias ; fake news ; polarization ; filter bubble ; lab experiments;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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