Susceptibility to Online Misinformation: A Systematic Meta-Analysis of Demographic and Psychological Factors

OSF

Abstract

Despite a surge of research into misinformation, it is largely unclear who falls for misinformation and why. We conducted a systematic individual participant data meta-analysis covering 256,337 unique choices made by 11,561 participants across 31 experiments. Our metaanalysis reveals the impact of key demographic and psychological factors on online misinformation veracity judgments. We also disentangle the ability to discern between true and false news (discrimination ability) from the response bias, that is, a tendency to label news as either true (true-news bias) or false (false-news bias). We find that older age, higher analytic thinking skills, and identifying as a Democrat are associated with higher discrimination ability. Older age and higher analytical thinking skills are also associated with a false-news bias (caution). In contrast, ideological congruency, motivated reflection, and familiarity are associated with a true-news bias (naïvety). Our results touch upon ongoing debates in the literature and provide critical insights that can help design targeted interventions.

Philipp Lorenz-Spreen
Philipp Lorenz-Spreen
Young Investigator

My research interests are causal inference in dynamic time series systems

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