Combating Fake News on Social Media with Source Ratings

The Effects of User and Expert Reputation Ratings

Bibliographic Data

ID23323904
AuthorsAntino Kim (0000-0002-2886-0892, Indiana University), Patricia Moravec (0000-0001-5896-5444, The University of Texas at Austin), Alan R Dennis (0000-0002-6439-6134)
Year2019
Volume36
Issue3
Pages931-968
Publication date2019-07-03
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Management Information Systems (JOURNAL)
Journal identifiersISSN: 0742-1222 • E-ISSN: 1557-928X
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/07421222.2019.1628921
OpenAlexW2782032413
LanguageEN
Citations received62
References cited54

As a remedy against fake news on social media, we examine the effectiveness of three different mechanisms for source ratings that can be applied to articles when they are initially published: expert rating (where expert reviewers fact-check articles, which are aggregated to provide a source rating), user article rating (where users rate articles, which are aggregated to provide a source rating), and user source rating (where users rate the sources themselves). We conducted two experiments and found that source ratings influenced social media users’ beliefs in the articles and that the rating mechanisms behind the ratings mattered. Low ratings, which would mark the usual culprits in spreading fake news, had stronger effects than did high ratings. When the ratings were low, users paid more attention to the rating mechanism, and, overall, expert ratings and user article ratings had stronger effects than did user source ratings. We also noticed a second-order effect, where ratings on some sources led users to be more skeptical of sources without ratings, even with instructions to the contrary. A user’s belief in an article, in turn, influenced the extent to which users would engage with the article (e.g., read, like, comment and share). Lastly, we found confirmation bias to be prominent; users were more likely to believe — and spread — articles that aligned with their beliefs. Overall, our results show that source rating is a viable measure against fake news and propose how the rating mechanism should be designed.

Business · Information source (mathematics) · Internet privacy · Order (exchange) · Political science · Rating system · Reputation · Skepticism · Social media · Statistics · World Wide Web · Computer Science · Media Influence and Politics · Misinformation and Its Impacts · Psychology · Spam and Phishing Detection

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Open DOISci-HubOpen Access