Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention

By Gordon Pennycook, J. McPhetres, Yunhao Zhang, Jackson G. Lu, David G. Rand. Psychology Science, 2020

1,527 citations recorded by the source corpus.

Across two studies with more than 1,700 U.S. adults recruited online, we present evidence that people share false claims about COVID-19 partly because they simply fail to think sufficiently about whether or not the content is accurate when deciding what to share. In Study 1, participants were far worse at discerning between true and false content when deciding what they would share on social media relative to when they were asked directly about accuracy. Furthermore, greater cognitive reflection and science knowledge were associated with stronger discernment. In Study 2, we found that a simple accuracy reminder at the beginning of the study (i.e., judging the accuracy of a non-COVID-19-related headline) nearly tripled the level of truth discernment in participants’ subsequent sharing intentions. Our results, which mirror those found previously for political fake news, suggest that nudging people to think about accuracy is a simple way to improve choices about what to share on social media.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/bc5facfd49ec7b635f2fe75a817def81cb9a1a24

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In Artificial Intelligence

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  4. Jay J. Van Bavel
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In Cognitive Neuroscience

  1. David G. Rand
  2. S. van der Linden
  3. J. Roozenbeek
  4. Gordon Pennycook
  5. Morten Moshagen
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  8. Ingo Zettler

In Sociology and Political Science

  1. J. Roozenbeek
  2. S. van der Linden
  3. David G. Rand
  4. Gordon Pennycook
  5. Jay J. Van Bavel
  6. Elizabeth Harris
  7. Sabrine Amri
  8. Esma Aïmeur

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