Exploring emotional discourses: The case of COVID-19 protests in the US media

Abstract

Emotions are involved in virtually every aspect of human cognition, including information processing and decision-making. Thus, to understand political conflict and policy decision-making more fully, we must strive to understand the role of emotions in these phenomena. This paper explores expressed emotions in protests related to the policy decisions around the COVID-19 pandemic. We collect and analyze data on expressed emotions from protests in four U.S. states covered in 185 articles from 66 newspapers. We use an integrated method analysis that incorporates elements of Discourse Network Analysis (DNA) and interpretive analysis of emotions. Our DNA analysis shows differing distributions of emotions across protests against government restrictions and for restrictions to protect vulnerable populations from COVID-19. From these distributions, fear emerges as one of the more prominent emotions linked to an actor’s role in the process and the context. We use interpretive analysis of emotions to understand the role of fear better. This paper contributes to the literature in two ways. First, we contribute empirically to the theoretical arguments to integrate structural, cultural, and relational analyses of emotions in politics. Second, we offer a rare combination of methods to code and analyze emotions in texts.