Appraisal Theory Predicts Emotions in the General, but Not in the Political Domain

Emotions, such as anger and anxiety, play a central role in political behavior and are extensively studied by political scientists. However, political science has largely adopted psychological theories of emotions without empirically testing their core assumptions in political contexts.In this paper, we focus on cognitive appraisal theory and test whether political emotions follow distinct appraisal patterns, and whether the underlying theoretical models accurately explain how discrete emotions emerge in political contexts. We conducted two surveys in the U.S. in 2022 and 2023. Participants recalled emotional experiences from either the personal or political domain, labeled their emotions, and rated the event along 18 cognitive appraisal dimensions. We then trained several models to predict the emotion label based on the reported appraisals.In non-political contexts, we can predict emotions based on the reported appraisals with high accuracy and discrete emotions align with theoretical appraisal patterns. However, in political contexts, negative emotions (anger, anxiety, despair) have overlapping appraisal profiles, and models perform consistently worse when trying to predict these emotions.These findings challenge the assumption that emotions function similarly in political and personal domains and suggest that existing appraisal-based models do not sufficiently capture political emotions. Our results highlight the need for revised theoretical frameworks that account for contextual differences in emotional processes within political science.