Veille Scientifique étudiante concernant la cognition partagée (SharedCognition) et la polarisation politique
Alimenté par : Claudia Dapino Ponel, Madeline Desmurs
Cette application est une plateforme collaborative de veille scientifique permettant d'importer des publications depuis PubMed, de suivre leur lecture, d'en extraire les éléments méthodologiques clés (protocole, variables, résultats), et de constituer une synthèse structurée pour faciliter la réalisation de revues de littérature.
Dernière synchronisation : 11/06/2026
JMIR Infodemiology . 2022;2 (1) :e29246
BACKGROUND: Amid the COVID-19 pandemic, social media have influenced the circulation of health information. Public health agencies often use Twitter to disseminate and amplify the propagation of such information. Still, exposure to local government-endorsed COVID-19 public health information does not make one immune to believing misinformation. Moreover, not all health information on Twitter is accurate, and some users may believe misinformation and disinformation just as much as those who endorse more accurate information. This situation is complicated, given that elected officials may pursue a political agenda of re-election by downplaying the need for COVID-19 restrictions. The politically polarized nature of information and misinformation on social media in the United States has fueled a COVID-19 infodemic. Because pre-existing political beliefs can both facilitate and hinder persuasion, Twitter users' belief in COVID-19 misinformation is likely a function of their goal inferences about their local government agencies' motives for addressing the COVID-19 pandemic.OBJECTIVE: We shed light on the cognitive processes of goal understanding that underlie the relationship between partisanship and belief in health misinformation. We investigate how the valence of Twitter users' goal inferences of local governments' COVID-19 efforts predicts their belief in COVID-19 misinformation as a function of their political party affiliation.METHODS: We conducted a web-based cross-sectional survey of US Twitter users who followed their state's official Department of Public Health Twitter account (n=258) between August 10 and December 23, 2020. Inferences about local governments' goals, demographics, and belief in COVID-19 misinformation were measured. State political affiliation was controlled.RESULTS: Participants from all 50 states were included in the sample. An interaction emerged between political party affiliation and goal inference valence for belief in COVID-19 misinformation (∆ =0.04; =4.78;