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How social and non-social information influence classification decisions: A computational modelling approach

Puskaric, Marin and von Helversen, Bettina and Rieskamp, Jörg. (2016) How social and non-social information influence classification decisions: A computational modelling approach. Quarterly Journal of Experimental Psychology, 70 (8). pp. 1516-1534.

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Official URL: http://edoc.unibas.ch/52916/

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Abstract

Social information such as observing others can improve performance in decision making. In particular, social information has been shown to be useful when finding the best solution on one's own is difficult, costly, or dangerous. However, past research suggests that when making decisions people do not always consider other people's behaviour when it is at odds with their own experiences. Furthermore, the cognitive processes guiding the integration of social information with individual experiences are still under debate. Here, we conducted two experiments to test whether information about other persons' behaviour influenced people's decisions in a classification task. Furthermore, we examined how social information is integrated with individual learning experiences by testing different computational models. Our results show that social information had a small but reliable influence on people's classifications. The best computational model suggests that in categorization people first make up their own mind based on the non-social information, which is then updated by the social information.
Faculties and Departments:07 Faculty of Psychology > Departement Psychologie > Society & Choice > Economic Psychology (Rieskamp)
UniBasel Contributors:Puskaric, Marin and von Helversen, Bettina and Rieskamp, Jörg
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Taylor & Francis
ISSN:1747-0218
e-ISSN:1747-0226
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:31 Oct 2017 09:26
Deposited On:31 Oct 2017 09:26

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