Behind the Stars: The Effects of News Source Ratings on Fake News in Social Media
38 Pages Posted: 22 Dec 2017 Last revised: 2 Jan 2018
Date Written: December 18, 2017
The rise of “fake news” has become a major concern for social media platforms and their users with many researchers working on approaches for fact checking of articles. Article fact-checking usually appears after a fake article has been widely read, so it has only limited effects. We examine the effectiveness of three different mechanisms for news source ratings that can be applied to news articles when they are initially published: expert article rating (where expert reviewers fact-check past articles, which are aggregated to provide a source rating), user article rating (where users rate past articles, which are aggregated to provide a source rating), and user source rating (where users rate the sources directly). We conducted an experiment with 590 social media users and found that all forms of rating influenced the user’s belief in the articles, with different rating mechanisms having varying levels of impact. Notably, expert article ratings and user article ratings have stronger effects than do user source ratings for low-rated sources, which are the usual culprits responsible for spreading disinformation. 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). In addition to these effects, we also found confirmation bias to be rampant; users were more likely to believe — and engage with — articles that aligned with their beliefs.
Keywords: Fake news, social media, article rating, source rating, expert rating, user rating
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