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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 na¨ively take signals at face value and account for neither the selection in 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," CAGE Online Working Paper Series 427, Competitive Advantage in the Global Economy (CAGE).
  • Handle: RePEc:cge:wacage:427
    as

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    File URL: https://warwick.ac.uk/fac/soc/economics/research/centres/cage/manage/publications/427-2019_pogorelskiy.pdf
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Buechel, Berno & Mechtenberg, Lydia, 2019. "The swing voter's curse in social networks," Games and Economic Behavior, Elsevier, vol. 118(C), pages 241-268.
    2. 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.
    3. van Gils, Freek & Müller, Wieland & Prüfer, Jens, 2020. "Big Data and Democracy," Discussion Paper 2020-003, Tilburg University, Tilburg Law and Economic Center.
    4. Marco Battaglini & Rebecca B. Morton & Eleonora Patacchini, 2020. "Social Groups and the Effectiveness of Protests," Working Papers 20200039, New York University Abu Dhabi, Department of Social Science, revised Feb 2020.
    5. Guy Aridor & Rafael Jiménez-Durán & Ro'ee Levy & Lena Song, 2024. "The Economics of Social Media," CESifo Working Paper Series 10934, CESifo.
    6. Boris Ginzburg, 2023. "Slacktivism," Journal of Theoretical Politics, , vol. 35(2), pages 126-143, April.
    7. 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.
    8. Felix Chopra & Ingar K. Haaland & Christopher Roth, 2019. "Do People Value More Informative News?," CESifo Working Paper Series 8026, CESifo.
    9. 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.
    10. Dugar, Subhasish & Shahriar, Quazi, 2023. "Lying for votes," Games and Economic Behavior, Elsevier, vol. 142(C), pages 46-72.
    11. 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.
    12. 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).
    13. 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 JEL Classification: C72; C91; C92; D72; D83; D85;
    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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