Discovering social groups via latent structure learning
| Autor: | Samuel J. Gershman, Hillard Thomas Pouncy, Mina Cikara, Tatiana Lau |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Experimental and Cognitive Psychology
Models Psychological Social Environment Choice Behavior 050105 experimental psychology Social group 03 medical and health sciences 0302 clinical medicine Developmental Neuroscience Similarity (psychology) Humans Learning 0501 psychology and cognitive sciences Computer Simulation Balance theory Social Behavior General Psychology Structure (mathematical logic) Group (mathematics) 05 social sciences Social environment Social Perception Psychology Attribution 030217 neurology & neurosurgery Mechanism (sociology) Cognitive psychology |
| Zdroj: | Journal of experimental psychology. General. 147(12) |
| ISSN: | 1939-2222 |
| Popis: | Humans form social coalitions in every society on earth, yet we know very little about how social group boundaries are learned and represented—especially in the absence of overt labels or visual cues to individuals’ group membership. Here we adopt a computational model of latent structure learning to move beyond explicit category labels and mere similarity as the sole inputs to social group representations, and to formalize an alternative process by which people create group representations. Four experiments examine (i) how evidence for group boundaries is accumulated in a consequential social context (i.e., learning about others’ political values); (ii) to what extent learning about these boundaries drives one’s own preferences and behavior as well as attributions about other agents in the environment; and (iii) whether these latent groups affect choice even in the presence of group labels that contradict the latent group structure. In contrast to models where social groups are learned solely via matching to group labels/stereotypes or dyadic similarity to the self, our results suggest that people integrate information about how agents in the environment relate to one another in addition to oneself to infer a posterior distribution over possible latent groupings. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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