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Social media, sentiment and public opinions: Evidence from #Brexit and #USElection

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  • Gorodnichenko, Yuriy
  • Pham, Tho
  • Talavera, Oleksandr

Abstract

This paper studies information diffusion in social media and the potential role of bots in influencing public opinions. Using Twitter data on the 2016 E.U. Referendum (“Brexit”) and the 2016 U.S. Presidential Election, we find that diffusion of information on Twitter is largely complete within 1–2 h. Stronger diffusion between agents with similar beliefs is consistent with the “echo chambers” view of social media. Our results are consistent the notion that bots could have a tangible effect on the tweeting activity of humans and that the degree of bots’ influence depends on whether bots provide information consistent with humans’ priors. Overall, our results suggest that the aggressive use of Twitter bots, coupled with the fragmentation of social media and the role of sentiment, could enhance political polarization.

Suggested Citation

  • Gorodnichenko, Yuriy & Pham, Tho & Talavera, Oleksandr, 2021. "Social media, sentiment and public opinions: Evidence from #Brexit and #USElection," European Economic Review, Elsevier, vol. 136(C).
  • Handle: RePEc:eee:eecrev:v:136:y:2021:i:c:s0014292121001252
    DOI: 10.1016/j.euroecorev.2021.103772
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    Cited by:

    1. Natalie-Anne Hall, 2022. "Understanding Brexit on Facebook: Developing Close-up, Qualitative Methodologies for Social Media Research," Sociological Research Online, , vol. 27(3), pages 707-723, September.
    2. Benjamin Monnery & François-Charles Wolff, 2023. "Is participatory democracy in line with social protest? Evidence from the French Yellow Vests movement," Public Choice, Springer, vol. 197(1), pages 283-309, October.
    3. Toke S. Aidt & Facundo Albornoz & Esther Hauk, 2019. "Foreign Influence and Domestic Policy: A Survey," Working Papers 1072, Barcelona School of Economics.
    4. Kai-Cheng Yang & Emilio Ferrara & Filippo Menczer, 2022. "Botometer 101: social bot practicum for computational social scientists," Journal of Computational Social Science, Springer, vol. 5(2), pages 1511-1528, November.
    5. Ehrmann, Michael & Wabitsch, Alena, 2022. "Central bank communication with non-experts – A road to nowhere?," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 69-85.
    6. Simon Rudkin & Lucy Barros & Paweł Dłotko & Wanling Qiu, 2024. "An economic topology of the Brexit vote," Regional Studies, Taylor & Francis Journals, vol. 58(3), pages 601-618, March.
    7. Toke S. Aidt & Facundo Albornoz & Esther Hauk, 2021. "Foreign Influence and Domestic Policy," Journal of Economic Literature, American Economic Association, vol. 59(2), pages 426-487, June.
    8. Rui Fan & Oleksandr Talavera & Vu Tran, 2018. "Does connection with @realDonaldTrump affect stock prices?," Working Papers 2018-07, Swansea University, School of Management.
    9. Rui Fan & Oleksandr Talavera & Vu Tran, 2020. "Social media bots and stock markets," European Financial Management, European Financial Management Association, vol. 26(3), pages 753-777, June.
    10. Tolga Buz & Gerard de Melo, 2021. "Should You Take Investment Advice From WallStreetBets? A Data-Driven Approach," Papers 2105.02728, arXiv.org.
    11. Suppawong Tuarob & Thanapon Noraset & Tanisa Tawichsri, 2022. "Using Large-Scale Social Media Data for Population-Level Mental Health Monitoring and Public Sentiment Assessment: A Case Study of Thailand," PIER Discussion Papers 169, Puey Ungphakorn Institute for Economic Research.
    12. Rui Fan & Oleksandr Talavera & Vu Tran, 2023. "Social media and price discovery: The case of cross‐listed firms," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(1), pages 151-167, February.
    13. Tolga Buz & Gerard de Melo, 2022. "Democratization of Retail Trading: Can Reddit's WallStreetBets Outperform Investment Bank Analysts?," Papers 2301.00170, arXiv.org.
    14. Ambrocio, Gene & Hasan, Iftekhar, 2022. "Belief polarization and Covid-19," Bank of Finland Research Discussion Papers 10/2022, Bank of Finland.
    15. Zixuan Weng & Aijun Lin, 2022. "Public Opinion Manipulation on Social Media: Social Network Analysis of Twitter Bots during the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(24), pages 1-17, December.
    16. Vivian Chu & Tatjana Dahlhaus & Christopher Hajzler & Pierre-Yves Yanni, 2023. "Digitalization: Implications for Monetary Policy," Discussion Papers 2023-18, Bank of Canada.
    17. Hartwig H. Hochmair & Gerhard Navratil & Haosheng Huang, 2023. "Perspectives on Advanced Technologies in Spatial Data Collection and Analysis," Geographies, MDPI, vol. 3(4), pages 1-5, November.
    18. Alexander Koch & Toan Luu Duc Huynh & Mei Wang, 2024. "News sentiment and international equity markets during BREXIT period: A textual and connectedness analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 5-34, January.
    19. 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.

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    More about this item

    Keywords

    Brexit; U.S. Election; Information diffusion; Echo chambers; Political Bots; Twitter;
    All these keywords.

    JEL classification:

    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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