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Exposure to the Russian Internet Research Agency foreign influence campaign on Twitter in the 2016 US election and its relationship to attitudes and voting behavior

Author

Listed:
  • Gregory Eady

    (University of Copenhagen)

  • Tom Paskhalis

    (Trinity College Dublin)

  • Jan Zilinsky

    (Technical University of Munich)

  • Richard Bonneau

    (New York University)

  • Jonathan Nagler

    (New York University)

  • Joshua A. Tucker

    (New York University)

Abstract

There is widespread concern that foreign actors are using social media to interfere in elections worldwide. Yet data have been unavailable to investigate links between exposure to foreign influence campaigns and political behavior. Using longitudinal survey data from US respondents linked to their Twitter feeds, we quantify the relationship between exposure to the Russian foreign influence campaign and attitudes and voting behavior in the 2016 US election. We demonstrate, first, that exposure to Russian disinformation accounts was heavily concentrated: only 1% of users accounted for 70% of exposures. Second, exposure was concentrated among users who strongly identified as Republicans. Third, exposure to the Russian influence campaign was eclipsed by content from domestic news media and politicians. Finally, we find no evidence of a meaningful relationship between exposure to the Russian foreign influence campaign and changes in attitudes, polarization, or voting behavior. The results have implications for understanding the limits of election interference campaigns on social media.

Suggested Citation

  • Gregory Eady & Tom Paskhalis & Jan Zilinsky & Richard Bonneau & Jonathan Nagler & Joshua A. Tucker, 2023. "Exposure to the Russian Internet Research Agency foreign influence campaign on Twitter in the 2016 US election and its relationship to attitudes and voting behavior," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-022-35576-9
    DOI: 10.1038/s41467-022-35576-9
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    References listed on IDEAS

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    1. Zeileis, Achim, 2004. "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i10).
    2. Andrew M. Guess & Brendan Nyhan & Jason Reifler, 2020. "Exposure to untrustworthy websites in the 2016 US election," Nature Human Behaviour, Nature, vol. 4(5), pages 472-480, May.
    3. Grolemund, Garrett & Wickham, Hadley, 2011. "Dates and Times Made Easy with lubridate," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i03).
    4. Kalla, Joshua L. & Broockman, David E., 2018. "The Minimal Persuasive Effects of Campaign Contact in General Elections: Evidence from 49 Field Experiments," American Political Science Review, Cambridge University Press, vol. 112(1), pages 148-166, February.
    5. Erin Hartman & F. Daniel Hidalgo, 2018. "An Equivalence Approach to Balance and Placebo Tests," American Journal of Political Science, John Wiley & Sons, vol. 62(4), pages 1000-1013, October.
    6. Carlisle Rainey, 2014. "Arguing for a Negligible Effect," American Journal of Political Science, John Wiley & Sons, vol. 58(4), pages 1083-1091, October.
    7. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
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    Cited by:

    1. Yara Kyrychenko & Tymofii Brik & Sander Linden & Jon Roozenbeek, 2024. "Social identity correlates of social media engagement before and after the 2022 Russian invasion of Ukraine," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Marius Dragomir & José Rúas-Araújo & Minna Horowitz, 2024. "Beyond online disinformation: assessing national information resilience in four European countries," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    3. Marcel Caesmann & Janis Goldzycher & Matteo Grigoletto & Lorenz Gschwent, 2024. "Censorship in democracy," ECON - Working Papers 446, Department of Economics - University of Zurich.

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