The Psychology of Fake News

• Published in: Trends in cognitive sciences Vol. 25; no. 5; pp. 388 - 402
• Main Authors: Pennycook, Gordon, Rand, David G.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.05.2021
• Subjects: attention; crowdsourcing; dual process theory; fake news; information sharing; misinformation; motivated reasoning; news media; social media; dual process theory; crowdsourcing; information sharing; misinformation; news media; motivated reasoning; attention; social media; fake news
• ISSN: 1364-6613; 1879-307X; 1879-307X
• DOI: 10.1016/j.tics.2021.02.007

We synthesize a burgeoning literature investigating why people believe and share false or highly misleading news online. Contrary to a common narrative whereby politics drives susceptibility to fake news, people are ‘better’ at discerning truth from falsehood (despite greater overall belief) when evaluating politically concordant news. Instead, poor truth discernment is associated with lack of careful reasoning and relevant knowledge, and the use of heuristics such as familiarity. Furthermore, there is a substantial disconnect between what people believe and what they share on social media. This dissociation is largely driven by inattention, more so than by purposeful sharing of misinformation. Thus, interventions can successfully nudge social media users to focus more on accuracy. Crowdsourced veracity ratings can also be leveraged to improve social media ranking algorithms. Recent evidence contradicts the common narrative that partisanship and politically motivated reasoning explain why people fall for 'fake news'.Poor truth discernment is linked to a lack of careful reasoning and relevant knowledge, as well as to the use of familiarity and source heuristics.There is also a large disconnect between what people believe and what they will share on social media, and this is largely driven by inattention rather than by purposeful sharing of misinformation.Effective interventions can nudge social media users to think about accuracy, and can leverage crowdsourced veracity ratings to improve social media ranking algorithms.