Is this my group or not? The role of ensemble coding of emotional expressions in group categorization

Contributors:
  1. Timothy Sweeny
  2. Emmanuel Shpigel

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Description: People have a remarkable ability to aggregate emotional expressions of individuals in a group into summary statistics (known as ensemble coding). What is not yet clear, however, is how ensemble coding of others’ emotions affects self-categorization as part of that group. To address this issue, we developed a task designed to reveal the influence of the mean and variance of group members’ emotions on participants’ self-categorization. In Study 1, we verified that self-categorization decreases when the group’s mean emotion is different from participants’ own emotional response. In Study 2, we established that people identify a group’s mean emotion more accurately when its variance is lower. Most important, in Study 3, we showed that even when the group mean is different from participants’ own emotions, participants prefer to self-categorize as members of groups with low emotional variance. Our studies show how visual indicators of a group’s emotion impact self-categorization.

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Details of registrations: Notice that the paper contains 2 registrations (which were done before a full understanding of the OSF infrastructure - our apologies for this messy structure). Belonging_bayesian_task (original name of the project) - which contains the pre-registration for Study 1. Group categorization - which contains the pre-registration for Study 3.

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