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
J Med Internet Res . 2021;23 (6) :e26692
BACKGROUND: The novel coronavirus pandemic continues to ravage communities across the United States. Opinion surveys identified the importance of political ideology in shaping perceptions of the pandemic and compliance with preventive measures.OBJECTIVE: The aim of this study was to measure political partisanship and antiscience attitudes in the discussions about the pandemic on social media, as well as their geographic and temporal distributions.METHODS: We analyzed a large set of tweets from Twitter related to the pandemic, collected between January and May 2020, and developed methods to classify the ideological alignment of users along the moderacy (hardline vs moderate), political (liberal vs conservative), and science (antiscience vs proscience) dimensions.RESULTS: We found a significant correlation in polarized views along the science and political dimensions. Moreover, politically moderate users were more aligned with proscience views, while hardline users were more aligned with antiscience views. Contrary to expectations, we did not find that polarization grew over time; instead, we saw increasing activity by moderate proscience users. We also show that antiscience conservatives in the United States tended to tweet from the southern and northwestern states, while antiscience moderates tended to tweet from the western states. The proportion of antiscience conservatives was found to correlate with COVID-19 cases.CONCLUSIONS: Our findings shed light on the multidimensional nature of polarization and the feasibility of tracking polarized opinions about the pandemic across time and space through social media data.