Regional and temporal patterns of partisan polarization during the COVID-19 pandemic in the United States and Canada - Zachary Yang; Anne Imouza; Maximilian Puelma Touzel; Cécile Amadoro; Gabrielle Desrosiers-Brisebois; Kellin Pelrine; Sacha Levy; Jean-François Godbout; Reihaneh Rabbany (PLoS ONE, 2026)
During the COVID-19 pandemic, public health measures emerged as highly polarizing topics in online discourse, with debates intensifying around specific policy implementations and events. This study introduces a novel computational approach to measure subnational and event-driven variation in partisan polarization and explores these dynamics across the United States and Canada. Analyzing over 50 million tweets from late 2020—a critical period of polarizing discourse during the pandemic’s early phase—we examine regional variations in discussions surrounding three key health interventions: lockdowns, masks, and vaccines. Our analysis reveals that politically conservative regions exhibited significantly higher levels of partisan polarization in both countries, with this effect particularly pronounced in the United States. We demonstrate a strong negative correlation between regional vaccination rates and the degree of polarization in vaccine-related discussions in the U.S., suggesting tangible public health implications of online partisan division. This relationship was notably weaker in Canada, pointing to important cross-national differences in how political polarization manifests and impacts health behaviors. By tracking the temporal evolution of polarization, we identify distinct spikes linked to specific political events and policy announcements. These polarization surges typically lasted only a few days, revealing the dynamic nature of online partisan discourse. The geographic heterogeneity in polarization patterns—with certain conservative states showing unexpectedly low polarization and some liberal states displaying high polarization—highlights the complex interplay between political ideology, policy implementation, and public response during health crises. While our polarization index reflects the discourse of politically engaged Twitter users, it nevertheless captures key dynamics of online debate that influence public narratives and align with observable regional outcomes. Our findings suggest that online discussions both reflect and potentially drive rapid changes in public opinion, with measurable consequences for regional public health outcomes. This computational framework for quantifying polarization provides a valuable tool for researchers and policymakers to understand, monitor, and potentially address partisan divisions during public health emergencies and beyond.