Setting the misinformation agenda: Modeling COVID-19 narratives in Twitter communities

Abstract

This research investigates the dynamics of COVID-19 misinformation spread on Twitter within the unique context of Finland. Employing cutting-edge methodologies including text classification, topic modeling, social network analysis, and correspondence analysis (CA), the study analyzes 1.6 million Finnish tweets from December 2019 to October 2022. Misinformation tweets are identified through text classification and grouped into topics using BERTopic modeling. Applying the Leiden algorithm, the analysis uncovers retweet and mention networks, delineating distinct communities within each. CA determines these communities’ topical focuses, revealing how various groups prioritized different misinformation narratives throughout the pandemic. The findings demonstrate that influential, diverse communities introduce new misinformation, which then spreads to niche groups. This agenda-setting effect is amplified by social media algorithms optimized for engagement. The results provide valuable insights into how online communities shape public discourse during crises through the strategic dissemination of misinformation.