Believe It or Not: A Network Analysis Investigating How Individuals Embrace False and True Statements during COVID-19

Abstract

As individuals make belief decisions on truths and falsehoods, a systematic organization of (mis)information emerges. In this study, we employ a network approach to illustrate how a sample of Americans share a cognitive network of false and true statements related to COVID-19. Moreover, we examine what factors are associated with the formation of misbeliefs. Findings from our US-based rolling cross-sectional survey data indicate that conservative groups exhibit a greater tendency to mix up false and true information than liberal groups. This tendency preserved across different time points, revealing more homogenously structured information networks of conservative groups compared to liberal groups. The benefits of a cognitive network framework that integrates structural perspectives into theories are discussed.

Keywords

cognitive network, conservative group, homogenous information network, network analysis, ideological asymmetry, misinformation, misbelief, COVID-19