Online identity and action discourse around the 2020 and 2024 U.S. presidential elections

Social psychology theories of collective action argue that shared social identity mediates coordinated behavior through interacting collective mental states, such as the perception of a common grievance, the corresponding corrective action norms, and the associated efficacy beliefs. Large-scale social media data make it possible to test these theories quantitatively, but operationalizing them in online settings remains challenging. We propose an operationalization that maps the theoretical mental states onto discourse and evaluates their temporal interdependence using trend analysis, stationarity tests, vector autoregression, and pathway analysis. We apply this framework to the communal discussion of alleged voter fraud in the ∼90 million social media posts around the 2020 and 2024 U.S. presidential elections. In 2020/2021, we observe a canonical interaction sequence that the theories suggest: grievance about the alleged electoral fraud predicts subsequent mutual validation, validation predicts shared identity, and identity predicts efficacy beliefs and action discourse. Overall, the results are consistent with a collective psychological alignment that strengthens in the runup to January 6, 2021. Conversely, the 2024/2025 results do not reliably support either the alignment or the canonical sequence. Instead, the relationships are often negative or weak: grievance can suppress efficacy, action can reduce grievance, and identity predicts validation without consistently predicting action. These contrasts show that the coupling among grievance, validation, identity, efficacy, and action in digital conversation is context-dependent rather than universal. By operationalizing psychological theories in online discourse, the study both confirms specific theoretical mechanisms behind collective action in one electoral context and identifies the conditions under which the mobilizing alignment fragments in another.Author summary: We adapt the existing theories of social identity formation and development to large-scale social media data. In connecting the theories with the data, we utilize standard time-series statistical methodologies. We apply our framework to the development of the social identity that arose from the discussion of electoral fraud in the wake of the 2020 U.S. presidential election on the right-wing extremist social media networks. This social identity potentially served as the foundation for the subsequent attack on the U.S. Capitol on January 6, 2021. Our findings support this hypothesis and the canonical developmental sequence wherein the mutual validation of a discussed common grievance leads to the formation of an associated common identity that, in turn, elicits calls for corrective action. On the other hand, this identity development does not occur around the 2024 election, probably due to the lack of the necessary stimulating societal factors during this later time.