Robert Kaufman, Aaron Broukhim, Michael Robert Haupt
Social media platforms enhance the propagation of online misinformation by providing large user bases with a quick means to share content. One way to disrupt the rapid dissemination of misinformation at scale is through warning tags, which label content as potentially false or misleading. However, past warning tag mitigation studies yield mixed results for diverse audiences. We hypothesize that personalizing warning tags to the individual characteristics of their diverse users may enhance mitigation effectiveness. To reach the goal of personalization, we need to understand how people differ and how those differences predict a person's attitudes and behaviors toward tags and tagged content. In this study, we leverage Amazon Mechanical Turk (n = 132) and undergraduate students (n = 112) to provide this foundational understanding. With all participants combined, we find attitudes towards warning tags and self-described behaviors are significantly influenced by factors such as Need for Cognitive Closure (NFCC), Political orientation, and Trust in Medical Scientists when controlled for covariates such as age and recruiting platform. Analyses of each sample further show that tag attitudes were influenced by Trust in Religious Leaders, and Big Five Inventory (BFI) traits for Openness and Conscientiousness. We synthesize these results into design insights and a future research agenda for more effective and personalized warning tags and misinformation mitigation strategies more generally.