Collective identity in collective action: evidence from the 2020 summer BLM protests

Abstract

Does collective identity drive protest participation? A long line of research argues that collective identity can explain why protesters do not free ride and how specific movement strategies are chosen. Quantitative studies, however, are inconsistent in defining and operationalizing collective identity, making it difficult to understand under what conditions and to what extent collective identity explains participation. In this paper, we clearly differentiate between interest and collective identity to isolate the individual level signals of collective action. We argue that these quantities have been conflated in previous research, causing over estimation of the role of collective identity in protest behavior. Using a novel dataset of Twitter users who participated in Black Lives Matter protests during the summer of 2020, we find that contingent on participating in a protest, individuals have higher levels of interest in BLM on the day of and the days following the protest. This effect diminishes over time. There is little observed effect of participation on subsequent collective identity. In addition, higher levels of interest in the protest increases an individuals chance of participating in a protest, while levels of collective identity do not have a significant effect. These findings suggest that collective identity plays a weaker role in driving collective action than previously suggested. We claim that this overestimation is a byproduct of the misidentification of interest as identity.

Large language models and political science

“…Text and language are information that have long been important for the study of political science. For example, textual data has been used in political science to study political party manifestos (Laver and Garry, 2000), political speeches (Grimmer and Stewart, 2013), legislator communications with constituents (Grimmer, 2013), and social movements (Kann et al, 2023). LLMs and other generative AI models can also be used for creating political content at scale (Zhang et al, 2023a) (see Figure 1).…”