IDEAS home Printed from https://ideas.repec.org/a/sae/amsocr/v87y2022i6p919-949.html

Online Conspiracy Groups: Micro-Bloggers, Bots, and Coronavirus Conspiracy Talk on Twitter

Author

Listed:
  • Henrich R. Greve
  • Hayagreeva Rao
  • Paul Vicinanza
  • Echo Yan Zhou

Abstract

Conspiracies are consequential and social, yet online conspiracy groups that consist of individuals (and bots) seeking to explain events or a system have been neglected in sociology. We extract conspiracy talk about the COVID-19 pandemic on Twitter and use the biterm topic model (BTM) to provide a descriptive baseline for the discursive and social structure of online conspiracy groups. We find that individuals enter these communities through a gateway conspiracy theory before proceeding to extreme theories, and humans adopt more diverse conspiracy theories than do bots. Event-history analyses show that individuals tweet new conspiracy theories, and tweet inconsistent theories simultaneously, when they face a threat posed by a rising COVID-19 case rate and receive attention from others via retweets. By contrast, bots are less responsive to rising case rates, but they are more consistent, as they mainly tweet about how COVID-19 was deliberately created by sinister agents. These findings suggest human beings are bricoleurs who use conspiracy theories to make sense of COVID-19, whereas bots are designed to create moral panic. Our findings suggest that conspiracy talk by individuals is defensive in nature, whereas bots engage in offense.

Suggested Citation

  • Henrich R. Greve & Hayagreeva Rao & Paul Vicinanza & Echo Yan Zhou, 2022. "Online Conspiracy Groups: Micro-Bloggers, Bots, and Coronavirus Conspiracy Talk on Twitter," American Sociological Review, , vol. 87(6), pages 919-949, December.
    • Handle: RePEc:sae:amsocr:v:87:y:2022:i:6:p:919-949
    DOI: 10.1177/00031224221125937
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/00031224221125937
    Download Restriction: no
    File URL: https://libkey.io/10.1177/00031224221125937?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Osmundsen, Mathias & Bor, Alexander & Vahlstrup, Peter Bjerregaard & Bechmann, Anja & Petersen, Michael Bang, 2021. "Partisan Polarization Is the Primary Psychological Motivation behind Political Fake News Sharing on Twitter," American Political Science Review, Cambridge University Press, vol. 115(3), pages 999-1015, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou Jialin & Wu Chaojin, 2025. "Exploring the Landscape of American Sociology: A Bibliometric Analysis of Top Journal Publications (2011–2022)," SAGE Open, , vol. 15(2), pages 21582440251, June.
    2. Chaitawat Boonjubun & Anil Duman & Marta Kahancová, 2025. "Can crisis corporatism protect vulnerable workers? Conceptual insights from a European perspective," Transfer: European Review of Labour and Research, , vol. 31(3), pages 277-292, August.
    3. Oshan Uluşan & İbrahim Özejder, 2024. "Navigating the Intersection of Post-Truth and Sustainability in Journalism: Challenges Facing Sustainable Journalism in Northern Cyprus Media," SAGE Open, , vol. 14(2), pages 21582440241, June.
    4. Yeonsin Ahn & Henrich R. Greve, 2025. "Cultural Spawning: Founders Bringing Organizational Cultures to Their Startup," Organization Science, INFORMS, vol. 36(1), pages 411-428, January.
    5. Mangiò, Federico & Pedeliento, Giuseppe & Wassler, Philipp & Williams, Nigel, 2025. "Discursively negotiating AI: A social representation theory approach to LLM-based chatbots," Technological Forecasting and Social Change, Elsevier, vol. 221(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zeng, Jing & Brennen, Scott Babwah, 2023. "Misinformation," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 12(4), pages 1-20.
    2. Joshua A. Confer & Allison M. Champ & Dorsa Amir & Hanna Schleihauf & Jan M. Engelmann, 2025. "Group membership biases children’s evaluation of evidence," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    3. Jacopo Marchetti & Antonio Mastrogiorgio, 2025. "Becoming fake: an evolutionary model of fake news," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 24(2), pages 929-945, December.
    4. François t'Serstevens & Roberto Cerina & Giulia Piccillo, 2024. "Mapping the Risk of Spreading Fake-News via Wisdom-of-the-Crowd & MrP," CESifo Working Paper Series 11138, CESifo.
    5. Yasushi Asako & Yoshio Kamijo & Daiki Kishishita & Masayuki Odora, 2026. "Fighting Fake News with Peer Feedback: Theory and Experiment," Working Papers 2531, Waseda University, Faculty of Political Science and Economics.
    6. James N. Druckman & Donald P. Green & Shanto Iyengar, 2023. "Does Affective Polarization Contribute to Democratic Backsliding in America?," The ANNALS of the American Academy of Political and Social Science, , vol. 708(1), pages 137-163, July.
    7. Raúl Rodríguez-Ferrándiz, 2023. "An Overview of the Fake News Phenomenon: From Untruth-Driven to Post-Truth-Driven Approaches," Media and Communication, Cogitatio Press, vol. 11(2), pages 15-29.
    8. Eugen Dimant, 2024. "Hate Trumps Love: The Impact of Political Polarization on Social Preferences," Management Science, INFORMS, vol. 70(1), pages 1-31, January.
    9. Adrian Kwek & Luke Peh & Josef Tan & Jin Xing Lee, 2023. "Distractions, analytical thinking and falling for fake news: A survey of psychological factors," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    10. Tiziana Assenza & Fabrice Collard & Patrick Fève & Stefanie Huber, 2024. "From Buzz to Bust: How Fake News Shapes the Business Cycle," Working Papers hal-04958375, HAL.
    11. Çiğdem Bozdağ & Suncem Koçer, 2022. "Skeptical Inertia in the Face of Polarization: News Consumption and Misinformation in Turkey," Media and Communication, Cogitatio Press, vol. 10(2), pages 169-179.
    12. Eugen Dimant, 2020. "Hate Trumps Love: The Impact of Political Polarization on Social Preferences," ECONtribute Discussion Papers Series 029, University of Bonn and University of Cologne, Germany.
    13. Mohsen Mosleh & David G. Rand, 2022. "Measuring exposure to misinformation from political elites on Twitter," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    14. Mason Youngblood & Joseph M. Stubbersfield & Olivier Morin & Ryan Glassman & Alberto Acerbi, 2023. "Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    15. Jana Lasser & Segun T. Aroyehun & Fabio Carrella & Almog Simchon & David Garcia & Stephan Lewandowsky, 2023. "From alternative conceptions of honesty to alternative facts in communications by US politicians," Nature Human Behaviour, Nature, vol. 7(12), pages 2140-2151, December.
    16. Santosh Vijaykumar & Michael Craig & Ricardo J. Wray & Xiaoyu Liu & Rachel Mann & Kristofor McCarty & Nidhi Nagabhatla, 2026. "Identifying information voids during weather-related disasters: case studies from the 2024 Europe floods and Florida’s hurricane helene," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 122(6), pages 1-28, March.
    17. Tom Buchanan & Rotem Perach & Deborah Husbands & Amber F Tout & Ekaterina Kostyuk & James Kempley & Laura Joyner, 2024. "Individual differences in sharing false political information on social media: Deliberate and accidental sharing, motivations and positive schizotypy," PLOS ONE, Public Library of Science, vol. 19(6), pages 1-37, June.
    18. Marta Serra-Garcia, 2026. "The Attention-Information Trade-Off," American Economic Review, American Economic Association, vol. 116(5), pages 1579-1610, May.
    19. Brian Knutson & Tiffany W Hsu & Michael Ko & Jeanne L Tsai, 2024. "News source bias and sentiment on social media," PLOS ONE, Public Library of Science, vol. 19(10), pages 1-17, October.
    20. Jens Foerderer, 2023. "Should we trust web-scraped data?," Papers 2308.02231, arXiv.org.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:amsocr:v:87:y:2022:i:6:p:919-949. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.