Political Affiliation and Mental Health During Crises: Insights from Online Communication

Abstract

The COVID-19 pandemic and its policies universally impacted the US population in 2020, leading to notable physical and psychological effects. This study investigates how political orientation influenced depressive symptoms before and after COVID-19 using a sample of Twitter users. We trained a machine learning model to classify tweets for depressive language and applied econometric modeling to examine depressive symptoms among Democrats and Republicans in blue and red states from January 2019 to March 2023. Our findings show that political views and partisan policies did not moderate COVID-19's impact on depressive symptoms. Instead, the differences in discussed topics and personal expectations increased depressive symptoms. This research has significant implications for policymakers, mental health professionals, and social media platforms.