Dynamics of Polarizing Rhetoric in Congressional Tweets

Abstract

Affective polarization is pervasive in modern US politics, and can be intensified by strategic messaging from members of Congress. But there are gaps in our knowledge of the dynamics of polarizing appeals from elected representatives on social media. We explore the usage of polarizing rhetoric by members of Congress on Twitter using the 4.9 million tweets sent by members of Congress from 2009 to 2020, coded for the presence of polarizing rhetoric via a novel and highly accurate application of supervised machine learning methods. Fitting with our expectations, we find that more ideologically extreme members, those from safer districts, and those who are not in the president’s party are more likely to send polarizing tweets, and that polarizing tweets garner more engagement, increasing campaign funding for more polarizing members.