Influence and Improvisation: Participatory Disinformation during the 2020 US Election
Open accessAbstract
The 2020 US election was accompanied by an effort to spread a false meta-narrative of widespread voter fraud. This meta-narrative took hold among a substantial portion of the US population, undermining trust in election procedures and results, and eventually motivating the events of 6 January 2021. We examine this effort as a domestic and participatory disinformation campaign in which a variety of influencers—including hyperpartisan media and political operatives—worked alongside ordinary people to produce and amplify misleading claims, often unwittingly. To better understand the nature of participatory disinformation, we examine three cases of misleading claims of voter fraud, applying an interpretive, mixed method approach to the analysis of social media data. Contrary to a prevailing view of such campaigns as coordinated and/or elite-driven efforts, this work reveals a more hybrid form, demonstrating both top-down and bottom-up dynamics that are more akin to cultivation and improvisation.
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These dynamics reinforce a broader shift from blunt repression towards more preventive, fine-grained strategies of control.
“These dynamics reinforce a broader shift from blunt repression towards more preventive, fine-grained strategies of control.67”
From The rise of authoritarian informationalism: escalating surveillance, manipulation, and control (2026) · cites this paper as [67]
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- Authors
- Starbird, K., DiResta, R., & DeButts, M.
- Affiliations
- University of Washington (US)
- Stanford University (US)
- Corresponding author
- Starbird, Kate
- Venue
- Social Media + Society
- Publisher
- SAGE Publications
- Published
- 2023-04
- Volume
- 9
- Issue
- 2
- ISSN
- 2056-3051 (ISSN-L)
- OpenAlex
- W4379800317
- Cited by
- 90
- References
- 30
- Citations by year
- 2026: 29 · 2025: 38 · 2024: 21 · 2023: 2
- FWCI
- 38.67
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Social Media + Society (publishedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Craig Newmark Philanthropies
- John S. and James L. Knight Foundation
- Division of Information and Intelligent Systems (1749815, 2120496)
- Omidyar Network
- William and Flora Hewlett Foundation
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Keywords
- 2020 US presidential election, disinformation campaigns, social media, influencers, January 6 Capitol attack, cultivation, improvisation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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