Program on Democracy and the Internet

Deception Detection Accuracy for Fake News Headlines on Social Media

In partnership with


The project examines fundamental psychological issues associated with false news and misinformation in the emerging media environment, including 1) the extent that people believe false news, and 2) how successfully people can distinguish false from real news. Drawing on theories from deception detection research, we have so far conducted two online studies: Study 1 found a deception bias for judging news headlines and an overall better-than-chance detection accuracy rate (58%). Political news headlines are more likely to be judged accurately than those related to science. Study 2 replicated and extended the findings in Study 1 in a social media context that tested two aspects of social endorsement: frequency and source of social endorsement. Study 2 found that high frequency social endorsement (e.g., many ‘likes’) not only increased perceptions of news veracity, but also decreased accuracy for false-true discrimination. We discuss the implications of these data in the current media environment and how social endorsement heuristics can affect perceptions of news credibility and detection accuracy on social media.

  • Mufan Luo, Department of Communication, Stanford University
  • Dave Markowitz, Department of Communication, Stanford University