From Dark to Light: The Many Shades of Sharing Misinformation Online

Open Access Journal | ISSN: 2183-2439

Article | Open Access

From Dark to Light: The Many Shades of Sharing Misinformation Online


  • Miriam J. Metzger Department of Communication, University of California, USA
  • Andrew J. Flanagin Department of Communication, University of California, USA
  • Paul Mena Writing Program, University of California, USA
  • Shan Jiang Khoury College of Computer Sciences, Northeastern University, USA
  • Christo Wilson Khoury College of Computer Sciences, Northeastern University, USA


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Abstract:  Research typically presumes that people believe misinformation and propagate it through their social networks. Yet, a wide range of motivations for sharing misinformation might impact its spread, as well as people’s belief of it. By examining research on motivations for sharing news information generally, and misinformation specifically, we derive a range of motivations that broaden current understandings of the sharing of misinformation to include factors that may to some extent mitigate the presumed dangers of misinformation for society. To illustrate the utility of our viewpoint we report data from a preliminary study of people’s dis/belief reactions to misinformation shared on social media using natural language processing. Analyses of over 2,5 million comments demonstrate that misinformation on social media is often disbelieved. These insights are leveraged to propose directions for future research that incorporate a more inclusive understanding of the various motivations and strategies for sharing misinformation socially in large-scale online networks.

Keywords:  credibility; fake news; misinformation; news sharing

Published:  


DOI: https://doi.org/10.17645/mac.v9i1.3409


© Miriam J. Metzger, Andrew J. Flanagin, Paul Mena, Shan Jiang, Christo Wilson. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.