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Effective response to pandemics requires coordinated adoption of mitigationmeasures, like masking and quarantines, to curb a virus's spread. However, asthe COVID-19 pandemic demonstrated, political divisions can hinder consensus onthe appropriate response. To better understand these divisions, our studyexamines a vast collection of COVID-19-related tweets. We focus on fivecontentious issues: coronavirus origins, lockdowns, masking, education, andvaccines. We describe a weakly supervised method to identify issue-relevanttweets and employ state-of-the-art computational methods to analyze morallanguage and infer political ideology. We explore how partisanship and morallanguage shape conversations about these issues. Our findings revealideological differences in issue salience and moral language used by differentgroups. We find that conservatives use more negatively-valenced moral languagethan liberals and that political elites use moral rhetoric to a greater extentthan non-elites across most issues. Examining the evolution and moralization ondivisive issues can provide valuable insights into the dynamics of COVID-19discussions and assist policymakers in better understanding the emergence ofideological divisions.

Pandemic Culture Wars: Partisan Differences in the Moral Language of COVID-19 Discussions