Pandemic Personas: Analyzing Identity Signals in COVID-19 Discourse on Twitter

Abstract

The first year of the COVID-19 pandemic coincided with significant social and political changes. This article presents an exploratory analysis of Twitter users’ self-representations in the context of COVID-19. While some identities remained stable throughout the year, others appear to have been influenced by external events such as the Black Lives Matter protests and the U.S. presidential election. We also examine how users’ political identities are expressed in tweets, finding that right-leaning users are more likely to mention left-leaning identities, although both conservative and liberal-leaning users showed increased out-group focus in the period leading up to and after the election. Our study provides a comprehensive overview of user personas in a critical discourse topic, shedding light on identity signaling on social media. We end by identifying several clear opportunities for future research on social identity self-presentation on social media.

This work was supported in part by the Knight Foundation and the Office of Naval Research grant MURI: Persuasion, Identity, & Morality in Social-Cyber Environments, N00014-21-12749. Additional support was provided by the Center for Computational Analysis of Social and Organizational Systems (CASOS) at Carnegie Mellon University. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Knight Foundation, Office of Naval Research, or the U.S. Government.