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  1. Emmanuel Shpigel

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Description: When exposed to others’ emotional responses, people often make rapid decisions as to whether these others are members of their group or not. These group categorization decisions have been shown to be extremely important to understanding group behavior. Yet, despite their prevalence and importance, we know very little about the attributes that shape these categorization decisions. To address this issue, we took inspiration from ensemble coding research and developed a task designed to reveal the influence of the mean and variance of group members’ emotions on participants’ group categorization. In Study 1, we verified that group categorization decreases when the group’s mean emotion is different from the participant’s own emotional response. In Study 2, we established that people identify a group’s mean emotion more accurately when its variance is low rather than high. In Studies 3 and 4, we showed that participants were more likely to self-categorize as members of groups with low emotional variance, even if their own emotions fell outside of the range of group emotions they saw, and that this preference is seen for judgements of both positive and negative group emotions. In Study 5, we showed that this unique preference for low group emotional variance is special to group categorization and does not appear in a more basic face categorization task. Our studies reveal unexplored and important tendencies in group categorization based on group emotions.


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Study 3 a: Online Replication of Study 3

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