How conformity can lead to polarised social behaviour.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
10 2021
Historique:
received: 20 05 2021
accepted: 05 10 2021
revised: 01 11 2021
pubmed: 21 10 2021
medline: 15 12 2021
entrez: 20 10 2021
Statut: epublish

Résumé

Learning social behaviour of others strongly influences one's own social attitudes. We compare several distinct explanations of this phenomenon, testing their predictions using computational modelling across four experimental conditions. In the experiment, participants chose repeatedly whether to pay for increasing (prosocial) or decreasing (antisocial) the earnings of an unknown other. Halfway through the task, participants predicted the choices of an extremely prosocial or antisocial agent (either a computer, a single participant, or a group of participants). Our analyses indicate that participants polarise their social attitude mainly due to normative expectations. Specifically, most participants conform to presumed demands by the authority (vertical influence), or because they learn that the observed human agents follow the norm very closely (horizontal influence).

Identifiants

pubmed: 34669694
doi: 10.1371/journal.pcbi.1009530
pii: PCOMPBIOL-D-21-00918
pmc: PMC8559952
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1009530

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Folco Panizza (F)

Molecular Mind Laboratory, IMT School for Advanced Studies Lucca, Italy.
Center for Mind/Brain Sciences, University of Trento, Mattarello (TN), Italy.

Alexander Vostroknutov (A)

Department of Economics (MPE), Maastricht University, Maastricht, the Netherlands.

Giorgio Coricelli (G)

Department of Economics, University of Southern California, Los Angeles, California, United States of America.
LaPsyDÉ, UMR CNRS 8240, La Sorbonne, Paris, France.

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