Online interaction and identity cue adoption: a large-scale analysis of hashtag adoption on Twitter

With online interactions becoming an integral part of everyday social life, there is a need to better understand the relationship between social interaction and identity expression in digital environments. This study examines whether online self-presentation, specifically the adoption of identity-related hashtags in Twitter bios, is systematically associated with observable interaction patterns. Utilizing a large-scale dataset encompassing approximately 63 million Twitter profiles and 292 million interactions, we implement a matched quasi-experimental design comparing users who interacted with hashtag-bearing accounts to similar users who did not. Our results show that users who interact with others who feature particular hashtags in their bios subsequently adopt those hashtags at substantially higher rates. Adoption likelihood increases with the number of interaction partners displaying a given hashtag, though with diminishing marginal effects, and the magnitude of these associations varies across identity content categories, being strongest for fan communities and weakest for political hashtags. These patterns are consistent with theories of social influence and suggest that online self-presentation is systematically related to the social contexts in which users are embedded. However, given the observational design of this study, alternative explanations for the observed associations cannot be fully excluded. Future experimental research is needed to clarify the mechanisms underlying these associations and to examine their implications for community formation and the dynamics of collective identity in online environments.