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Social Media, Sentiment and Public Opinions: Evidence from #Brexit and #USElection

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  • Yuriy Gorodnichenko
  • Tho Pham
  • Oleksandr Talavera

Abstract

This paper studies information diffusion in social media and the role of bots in shaping 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 hours. Stronger interactions across agents with similar beliefs are consistent with the “echo chambers” view of social media. Bots have a tangible effect on the tweeting activity of humans but 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 contribute to the vote outcomes.

Suggested Citation

  • Yuriy Gorodnichenko & Tho Pham & Oleksandr Talavera, 2018. "Social Media, Sentiment and Public Opinions: Evidence from #Brexit and #USElection," NBER Working Papers 24631, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:24631
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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. 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.
    7. Rui Fan & Oleksandr Talavera & Vu Tran, 2018. "Does connection with @realDonaldTrump affect stock prices?," Working Papers 2018-07, Swansea University, School of Management.
    8. 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.
    9. Pawel Dlotko & Lucy Minford & Simon Rudkin & Wanling Qiu, 2019. "An Economic Topology of the Brexit vote," Papers 1909.03490, arXiv.org, revised Dec 2021.
    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.
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    More about this item

    JEL classification:

    • 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
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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