Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic.

ABSTRACT: COVID-19 represents the most severe global crisis to date whose public conversation can be studied in real time. To do so, we use a data set of over 350 million tweets and retweets posted by over 26 million English speaking Twitter users from January 13 to June 7, 2020. We characterize the retweet network to identify spontaneous clustering of users and the evolution of their interaction over time in relation to the pandemic's emergence. We identify several stable clusters (super-communities), and are able to link them to international groups mainly involved in science and health topics, national elites, and political actors. The science- and health-related super-community received disproportionate attention early on during the pandemic, and was leading the discussion at the time. However,

SUBMITTER: Durazzi F 

PROVIDER: S-EPMC8490394 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature