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Partisan public health: how does political ideology influence support for COVID-19 related misinformation?

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  • Nicholas Francis Havey

    (University of California, Los Angeles)

Abstract

This study analyzes over 4000 tweets related to six misinformation topics about the COVID-19 pandemic: the use of hydroxychloroquine as treatment, the use of bleach as a preventative measure, Bill Gates intentionally causing the virus, the Chinese Communist Party intentionally causing the virus, and the Deep State causing the virus to ruin the economy and threaten President Trump’s reelection chances. Across 5 of 6 topics (excluding bleach), conservatives dominate the discourse on Twitter. Conservatives are also more likely than their liberal peers to believe in and push conspiracy theories that the Chinese Communist Party, Bill Gates, and the Deep State are working in conjunction to infect the population and enact a surveillance state. Pandemic related misinformation has previously been associated with decreased adherence to public health recommendations and adverse health effects and evidence from the current pandemic indicates that adherence to public health recommendations is starkly partisan. This study suggests that the political and informational polarization further facilitated by social media platforms such as Twitter may have dire consequences for public health.

Suggested Citation

  • Nicholas Francis Havey, 2020. "Partisan public health: how does political ideology influence support for COVID-19 related misinformation?," Journal of Computational Social Science, Springer, vol. 3(2), pages 319-342, November.
    • Handle: RePEc:spr:jcsosc:v:3:y:2020:i:2:d:10.1007_s42001-020-00089-2
    DOI: 10.1007/s42001-020-00089-2
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    1. Fabiana Zollo & Petra Kralj Novak & Michela Del Vicario & Alessandro Bessi & Igor Mozetič & Antonio Scala & Guido Caldarelli & Walter Quattrociocchi, 2015. "Emotional Dynamics in the Age of Misinformation," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-22, September.
    2. Christensen, Darin & Garfias, Francisco, 2018. "Can You Hear Me Now? How Communication Technology Affects Protest and Repression," Quarterly Journal of Political Science, now publishers, vol. 13(1), pages 89-117, March.
    3. Cynthia Chew & Gunther Eysenbach, 2010. "Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-13, November.
    4. Shadi Shahsavari & Pavan Holur & Tianyi Wang & Timothy R. Tangherlini & Vwani Roychowdhury, 2020. "Conspiracy in the time of corona: automatic detection of emerging COVID-19 conspiracy theories in social media and the news," Journal of Computational Social Science, Springer, vol. 3(2), pages 279-317, November.
    5. Steinert-Threlkeld, Zachary C., 2017. "Spontaneous Collective Action: Peripheral Mobilization During the Arab Spring," American Political Science Review, Cambridge University Press, vol. 111(2), pages 379-403, May.
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    Cited by:

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    2. Emilio Ferrara & Stefano Cresci & Luca Luceri, 2020. "Misinformation, manipulation, and abuse on social media in the era of COVID-19," Journal of Computational Social Science, Springer, vol. 3(2), pages 271-277, November.
    3. van Mulukom, Valerie & Pummerer, Lotte J. & Alper, Sinan & Bai, Hui & Čavojová, Vladimíra & Farias, Jessica & Kay, Cameron S. & Lazarevic, Ljiljana B. & Lobato, Emilio J.C. & Marinthe, Gaëlle & Pavela, 2022. "Antecedents and consequences of COVID-19 conspiracy beliefs: A systematic review," Social Science & Medicine, Elsevier, vol. 301(C).
    4. Federica Maria Magarini & Margherita Pinelli & Arianna Sinisi & Silvia Ferrari & Giovanna Laura De Fazio & Gian Maria Galeazzi, 2021. "Irrational Beliefs about COVID-19: A Scoping Review," IJERPH, MDPI, vol. 18(19), pages 1-21, September.
    5. Waseem Ahmad & Bang Wang & Philecia Martin & Minghua Xu & Han Xu, 2023. "Enhanced sentiment analysis regarding COVID-19 news from global channels," Journal of Computational Social Science, Springer, vol. 6(1), pages 19-57, April.
    6. Laura Colautti & Alice Cancer & Sara Magenes & Alessandro Antonietti & Paola Iannello, 2022. "Risk-Perception Change Associated with COVID-19 Vaccine’s Side Effects: The Role of Individual Differences," IJERPH, MDPI, vol. 19(3), pages 1-14, January.
    7. Michael Becher & Daniel Stegmueller & Sylvain Brouard & Eric Kerrouche, 2021. "Ideology and compliance with health guidelines during the COVID‐19 pandemic: A comparative perspective," Social Science Quarterly, Southwestern Social Science Association, vol. 102(5), pages 2106-2123, September.
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    9. Tung, Hans H. & Chang, Teng-Jen & Lin, Ming-Jen, 2022. "Political ideology predicts preventative behaviors and infections amid COVID-19 in democracies," Social Science & Medicine, Elsevier, vol. 308(C).
    10. Hao Xu & Smitha Muthya Sudheendra & Jisu Huh & Aadesh Salecha & Jaideep Srivastava, 2024. "Influence of emotions on coping behaviors in crisis: a computational analysis of the COVID-19 outbreak," Journal of Computational Social Science, Springer, vol. 7(2), pages 1599-1623, October.
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