(Don’t) Stop Believing: A Signal Detection Approach to Risk and Protective Factors for Engagement with Politicized (Mis)Information in Social Media

Prior misinformation research often lacks comparisons with the processing of true information and specifically focuses on the dangers of right-wing or conservative misinformation. By employing a signal detection framework, this research addresses the ability to discern between true and false (discrimination sensitivity) as well as the tendency to prefer belief-congruent messages (confirmation bias) and reject belief-incongruent messages (disconfirmation bias), regardless of veracity, and aims to provide a comprehensive view on the ideological and cognitive factors that promote or inhibit engagement with politicized (mis)information across the political spectrum. In a pre-registered online experiment (N = 992), participants evaluated 16 social media posts (true vs. false, supporting left-wing vs. right-wing views) with regard to perceived credibility. Results identified the dark factor of personality and social media usage as risk factors that were connected to lower discrimination sensitivity. With regard to political orientation, bias occurred on both sides of the political spectrum: Rightists exhibited a stronger confirmation bias, while leftists were more likely to reject belief-incongruent messages even if they were true (higher disconfirmation bias). These findings highlight the relevance of unpacking (mis)information-related behavior into a more nuanced approach.