Social movement theorists have highlighted the importance of accounting for the fluidity of collective identities and the ways in which they change over time. Capitalizing on the availability of social media data and the shift from collective to connective action, new methods can be used to model identity change over a medium-to-long time span. We analyze Facebook data to make the case that a complex and longitudinal approach to the study of collective identity is not only possible but also necessary. Our analyses explore the formation and transformation of identity in the context of a local branch of the Gilets Jaunes (Yellow Vests) movement in France. By employing a mixed-method design that combines automated topic modeling, content analysis, and dictionary-based linguistic inquiry, we show how collective identities are discussed through complex and conflictual processes that form perpetual identity work.

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