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

Author

Listed:
  • Yuriy Gorodnichenko

    (Department of Economics, University of California (Berkeley))

  • Tho Pham

    () (School of Management, Swansea University)

  • Oleksandr Talavera

    () (School of Management, Swansea University)

Abstract

This paper studies information diffusion in social media and the role of information dissemination in shaping public opinions. Using Twitter data on the 2016 EU Referendum and the 2016 US Presidential Election, we find that information about these two events is spread quickly on Twitter, most likely within 1-2 hours. There are also interactions among different types of Twitter agents in spreading information with a considerable spillover from bot to human tweeting activities. However, the degree of influence depends on whether bots provide consistent information with humans' priors. This finding lends support to the "echo chambers" effect on Twitter that Twitter users are more likely to expose to information supporting their own views while ignore the opposite information. Further examination shows that sentiment matters in information acquiring and sharing. Overall, our results suggest that the aggressive use of Twitter bots, coupled by the fragmentation of social media and the role of sentiment, increases the polarization of public opinions about the EU Referendum and the US Election.

Suggested Citation

  • Yuriy Gorodnichenko & Tho Pham & Oleksandr Talavera, 2018. "Social media, sentiment and public opinions: Evidence from #Brexit and #USElection," Working Papers 2018-01, Swansea University, School of Management.
  • Handle: RePEc:swn:wpaper:2018-01
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    File URL: https://rahwebdav.swan.ac.uk/repec/pdf/WP2018-01.pdf
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    References listed on IDEAS

    as
    1. Alan S. Gerber & Dean Karlan & Daniel Bergan, 2009. "Does the Media Matter? A Field Experiment Measuring the Effect of Newspapers on Voting Behavior and Political Opinions," American Economic Journal: Applied Economics, American Economic Association, vol. 1(2), pages 35-52, April.
    2. Kewei Hou, 2007. "Industry Information Diffusion and the Lead-lag Effect in Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1113-1138.
    3. Stefano DellaVigna & Ethan Kaplan, 2007. "The Fox News Effect: Media Bias and Voting," The Quarterly Journal of Economics, Oxford University Press, vol. 122(3), pages 1187-1234.
    4. Matthew Gentzkow & Jesse M. Shapiro, 2011. "Ideological Segregation Online and Offline," The Quarterly Journal of Economics, Oxford University Press, vol. 126(4), pages 1799-1839.
    5. Eszter Hargittai & Jason Gallo & Matthew Kane, 2008. "Cross-ideological discussions among conservative and liberal bloggers," Public Choice, Springer, vol. 134(1), pages 67-86, January.
    6. Stefano Della Vigna & Ruben Enikolopov & Vera Mironova & Maria Petrova & Ekaterina Zhuravskaya, 2014. "Cross-Border Media and Nationalism: Evidence from Serbian Radio in Croatia," American Economic Journal: Applied Economics, American Economic Association, vol. 6(3), pages 103-132, July.
    7. Giuseppe Cavaliere & Peter C. B. Phillips & Stephan Smeekes & A. M. Robert Taylor, 2015. "Lag Length Selection for Unit Root Tests in the Presence of Nonstationary Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 34(4), pages 512-536, April.
    8. Halberstam, Yosh & Knight, Brian, 2016. "Homophily, group size, and the diffusion of political information in social networks: Evidence from Twitter," Journal of Public Economics, Elsevier, vol. 143(C), pages 73-88.
    9. Stefanie Haustein & Timothy D. Bowman & Kim Holmberg & Andrew Tsou & Cassidy R. Sugimoto & Vincent Larivière, 2016. "Tweets as impact indicators: Examining the implications of automated “bot” accounts on Twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(1), pages 232-238, January.
    10. Matthew Gentzkow, 2006. "Television and Voter Turnout," The Quarterly Journal of Economics, Oxford University Press, vol. 121(3), pages 931-972.
    11. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
    12. Joseph E. Engelberg & Christopher A. Parsons, 2011. "The Causal Impact of Media in Financial Markets," Journal of Finance, American Finance Association, vol. 66(1), pages 67-97, February.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Tribalism, Terranism, and Technology: The Pitfalls and Promises of Globalization
      by Jason Barr in Building the skyline on 2018-10-19 12:14:07

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    Cited by:

    1. Rui Fan & Oleksandr Talavera & Vu Tran, 2018. "Social media bots and stock markets," Working Papers 2018-30, Swansea University, School of Management.
    2. Rui Fan & Oleksandr Talavera & Vu Tran, 2018. "Does connection with @realDonaldTrump affect stock prices?," Working Papers 2018-07, Swansea University, School of Management.

    More about this item

    Keywords

    Brexit; US Election; Information diffusion; Echo chambers; Political Bots; Twitter;

    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
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law

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