"Here's Your Evidence": False Consensus in Public Twitter Discussions of COVID-19 Science

The COVID-19 pandemic brought about an extraordinary rate of scientific papers on the topic that were discussed among the general public, although often in biased or misinformed ways. In this paper, we present a mixed-methods analysis aimed at examining whether public discussions were commensurate with the scientific consensus on several COVID-19 issues. We estimate scientific consensus based on samples of abstracts from preprint servers and compare against the volume of public discussions on Twitter mentioning these papers. We find that anti-consensus posts and users, though overall less numerous than pro-consensus ones, are vastly over-represented on Twitter, thus producing a false consensus effect. This transpires with favorable papers being disproportionately amplified, along with an influx of new anti-consensus user sign-ups. Finally, our content analysis highlights that anti-consensus users misrepresent scientific findings or question scientists' integrity in their efforts to substantiate their claims.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2024-11-07
DOI
https://doi.org/10.1145/3687010
Citations
1
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
1.13
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article

"Here's Your Evidence": False Consensus in Public Twitter Discussions of COVID-19 Science

Emiliano De Cristofaro, Alexandros Efstratiou, Jeremy Blackburn, Satrio Baskoro Yudhoatmojo et al.
1 citations
Proceedings of the ACM on Human-Computer Interaction
Misinformation and Its Impacts
1.13
article

"Here's Your Evidence": False Consensus in Public Twitter Discussions of COVID-19 Science

Emiliano De Cristofaro, Alexandros Efstratiou, Jeremy Blackburn, Satrio Baskoro Yudhoatmojo, Marina Efstratiou
article en
1 citations

Abstract

The COVID-19 pandemic brought about an extraordinary rate of scientific papers on the topic that were discussed among the general public, although often in biased or misinformed ways. In this paper, we present a mixed-methods analysis aimed at examining whether public discussions were commensurate with the scientific consensus on several COVID-19 issues. We estimate scientific consensus based on samples of abstracts from preprint servers and compare against the volume of public discussions on Twitter mentioning these papers. We find that anti-consensus posts and users, though overall less numerous than pro-consensus ones, are vastly over-represented on Twitter, thus producing a false consensus effect. This transpires with favorable papers being disproportionately amplified, along with an influx of new anti-consensus user sign-ups. Finally, our content analysis highlights that anti-consensus users misrepresent scientific findings or question scientists' integrity in their efforts to substantiate their claims.

Proceedings of the ACM on Human-Computer InteractionVol. 8(CSCW2)
University of California, Riverside (US), Binghamton University (US), University College London (GB)
Good health and well-being
Openalex Percentile: Top 15%
Misinformation and Its Impacts
1.13
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