A Systematic Meta-Analysis of Demographic and Psychological Factors Underlying Online Misinformation Veracity Judgements
Tue-HS3-Talk IV-02
Presented by: Mubashir Sultan
Many scholars agree that misinformation poses a serious threat to democracy, noting that the way(s) it is impacting the democratic process remains mostly unknown. As a response, a large effort is currently underway to uncover factors that make one vulnerable to misinformation. While this body of research has been instrumental for our understanding, the literature is fragmented, making it difficult to derive general conclusions about the importance and comparative strength of different factors. Research on key standard demographics (such as age, gender, education, and political identity) and psychological factors (such as analytical thinking, partisan bias, motivated reflection, and familiarity) is largely scattered, and in some cases, not frequently reported. Here, we aim to aggregate these disparate findings by conducting a systematic meta-analysis, synthesising the evidence for the impact of general demographic and psychological factors on misinformation veracity judgements. We carry out a reanalysis of raw data using signal detection theory (SDT) for statistical inference. Critically, SDT provides a more nuanced understanding of news veracity, as it can distinguish between one’s ability to judge between true and false news (i.e., discrimination ability) and one’s response tendencies (i.e., response bias; the likelihood of selecting one option [true news] over another [false news]). Overall, with this systematic meta-analysis, we aim to better understand the role of the above-mentioned demographic and psychological factors on misinformation veracity judgements, ultimately helping to inspire further theory and intervention building.
Keywords: analytical thinking, false news, illusory truth effect, misinformation, motivated reflection, partisan bias, signal detection theory