Why Partisans Feel Hated: Distinct Static and Dynamic Relationships with Animosity Meta-Perceptions

Partisans hold inaccurate perceptions of the other side. What drives these inaccuracies? We address this question with a focus on partisan animosity meta-perceptions (i.e., how much a partisan believes opposing partisans hate them). We argue that predictors can relate to meta-perceptions statically (e.g., at a specific point in time, do partisans who post more about politics on social media differ in their meta-perceptions relative to partisans who post less?) or dynamically (e.g., does a partisan who increases their social media political posting between two defined time points change their meta-perceptions accordingly?). Using panel data from the 2020 U.S. presidential election, we find variables display distinct static and dynamic relationships with meta-perceptions. Notably, between individuals, posting on-line exhibits no (static) relationship with meta-perceptions while, within individuals, those who increased their postings over time (dynamically) became more accurate. The results make clear that overly general statements about meta-perceptions and their predictors, including social media activity, are bound to be wrong. How meta-perceptions relate to other factors often depends on contextual circumstances at a given time.