Detecting Covid-19 Fake News on Twitter/X in French: Deceptive Writing Strategies

Ming Ming Chiu, Alex Morakhovski, Zhan Wang and Jeong-Nam Kim
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Ming Ming Chiu: Analytics\Assessment Research Center, The Education University of Hong Kong, Hong Kong / Department of Special Education and Counseling, The Education University of Hong Kong, Hong Kong
Alex Morakhovski: Analytics\Assessment Research Center, The Education University of Hong Kong, Hong Kong
Zhan Wang: Analytics\Assessment Research Center, The Education University of Hong Kong, Hong Kong
Jeong-Nam Kim: Gaylord College of Journalism and Mass Communication, University of Oklahoma, USA / Debiasing & Lay Informatics (DaLI) Lab, USA

Media and Communication, 2025, vol. 13

Abstract: Many who believed Covid-19 fake news eschewed vaccines, masks, and social distancing; got unnecessarily infected; and died. To detect such fake news, we follow deceptive writing theory and link French hedges and modals to validity. As hedges indicate uncertainty, fake news writers can use it to include falsehoods while shifting responsibility to the audience. Whereas devoir (must) emphasizes certainty and truth, falloir (should, need) implies truth but emphasizes external factors, allowing writers to shirk responsibility. Pouvoir (can) indicates possibility, making it less tied to truth or falsehood. We tested this model with 50,000 French tweets about Covid-19 during March–August 2020 via mixed response analysis. Tweets with hedges or the modal falloir were more likely than others to be false, those with devoir were more likely to be true, and those with pouvoir showed no clear link to truth. Tweets of users with verification, more followers, or fewer status updates were more likely to be true. These results extend deceptive writing theory and inform fake news detection algorithms and media literacy instruction.

Keywords: Covid-19; deception; disinformation; fake news; French; hedges; modals; uncertainty (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:cog:meanco:v13:y:2025:a:9483

DOI: 10.17645/mac.9483

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