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Cited by 48Misinformation and Its ImpactsCommunication and COVID-19 ImpactComplex Network Analysis Techniques

Demographics and topics impact on the co-spread of COVID-19 misinformation and fact-checks on Twitter

Open access
Burel, Grégoire, Farrell, Tracie, Alani, Harith·2021·Information Processing & Management
DOI 10.1016/j.ipm.2021.102732PMC PMC8425034
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Abstract

Correcting misconceptions and false beliefs are important for injecting reliable information about COVID-19 into public discourse, but what impact does this have on the continued proliferation of misinforming claims? Fact-checking organisations produce content with the aim of reducing misinformation spread, but our knowledge of its impact on misinformation for particular topics and demographics is limited. In this article, we explore the relation between misinformation and fact-checking spread during the COVID-19 pandemic for different topics, user demographics and attributes. We specifically follow misinformation and fact-checks emerging from December 2019 until the 4th of January 2021 on Twitter. Using a combination of spread variance analysis, impulse response modelling and causal analysis, we highlight the bidirectional, weak causation spread behaviour between misinformation and fact-checks. Although we observe that fact-checks about COVID-19 are appearing fairly quickly after misinformation is circulated, its ability to reduce overall misinformation spread appears to be limited. This is especially visible for misinformation about conspiracy theories and the causes of the virus.

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  • Research has demonstrated that misinformation spreads more widely, rapidly, and deeply than fact-checks or truthful information on social media.

    “Research has demonstrated that misinformation spreads more widely, rapidly, and deeply than fact-checks or truthful information on social media (Burel et al., 2021; Mendoza et al., 2023; Shao et al., 2018; Vosoughi et al., 2018).”

    From "Just Asking Questions": Doing Our Own Research on Conspiratorial Ideation by Generative AI Chatbots (2026) · cites this paper as Burel et al., 2021

    The Introduction says misinformation spreads faster than true information, and the Discussion (“Fact-checks and misinformation spread behaviour”; page unavailable) reports that misinformation spread much more than fact-checks, accounting for 70% of spread in this study. The paper does not establish that it spreads more deeply, or that it spreads faster than fact-checks; it says fact-checks followed a similar temporal pattern. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • As conspiracy theories can be amplified so quickly on social media, there is less time for authoritative sources to have published fact-checks.

    “As conspiracy theories can be amplified so quickly on social media, there is less time for authoritative sources to have published fact-checks-our rationale for inclusion was to see if this would influence chatbot results (Burel et al., 2021; Schatto-Eckrodt et al., 2024).”

    From "Just Asking Questions": Doing Our Own Research on Conspiratorial Ideation by Generative AI Chatbots (2026) · cites this paper as Burel et al., 2021

    The Introduction (page unavailable) says COVID-19 misinformation spreads rapidly, supporting the claim’s premise. But the Topic and Global results (pages unavailable) report a quick fact-checking response when fact-checks are available; they do not establish that authoritative sources have too little time to publish them. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Burel, G., Farrell, T., & Alani, H.
Affiliations
The Open University (GB)
Corresponding author
Burel, Grégoire
ORCID
Venue
Information Processing & Management
Publisher
Elsevier BV
Published
2021-11
Volume
58
Issue
6
Pages
102732
ISSN
  • 0020-0271 (ISSN-L)
  • 0306-4573
DOI
10.1016/j.ipm.2021.102732
PMC
PMC8425034
OpenAlex
W3197363250
Cited by
48
References
10
Citations by year
2026: 3 · 2025: 12 · 2024: 8 · 2023: 11 · 2022: 14
FWCI
11.43
Type
journal article
Language
en
Open access
Licence
Locations
  • Information Processing & Management (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Open Research Online - ORO (The Open University) (acceptedVersion)
Funders
  • Horizon 2020 Framework Programme
  • Horizon 2020 (101003606, 770302)
Topics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Social Sciences › Communication › Communication and COVID-19 Impact
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
Keywords
COVID-19 misinformation, Twitter, misinformation spread, user demographics, conspiracy theories, misinformation correction, social media

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