How social and non-social information influence classification decisions: A computational modelling approach.
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.
a Center for Economic Psychology, Department of Psychology , University of Basel , Basel , Switzerland.
Marin
M
Puskaric
a Center for Economic Psychology, Department of Psychology , University of Basel , Basel , Switzerland.
Bettina
B
von Helversen
a Center for Economic Psychology, Department of Psychology , University of Basel , Basel , Switzerland.
Jörg
J
Rieskamp
D000293:Adolescent; D000328:Adult; D000704:Analysis of Variance; D001288:Attention / Q000502:physiology*; D015982:Bias; D003198:Computer Simulation; D003210:Concept Formation / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D005260:Female; D007839:Functional Laterality; D006801:Humans; D007600:Judgment; D008297:Male; D010775:Photic Stimulation; D011932:Reading; D012938:Social Perception; D014796:Visual Perception; D055815:Young Adult
Classification; Computational modelling; Decision making; Social learning