Blanchet, Adrien, Cezera, Stéphane, Escobedo, Ramon, Jayles, Bertrand, Kameda, Tatsuya, Kim, Hye-rin, Sire, Clément and Théraulaz, Guy (2017) How social information can improve estimation accuracy in human groups. Proceedings of the National Academy of Sciences of the United States of America (PNAS), vol. 114 (n° 47).

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Identification Number : 10.1073/pnas.1703695114

Abstract

Digital technologies deeply impact the way that people interact. Therefore, it is crucial to understand how social influence affects individual and collective decision-making. We performed experiments where subjects had to answer questions and then revise their opinion after knowing the average opinion of some previous participants. Moreover, unbeknownst to the subjects, we added a controlled number of virtual participants always giving the true answer, thus precisely controlling social information. Our experiments and data-driven model show how social influence can help a group of individuals collectively improve its performance and accuracy in estimation tasks depending on the quality and quantity of information provided. Our model also shows how giving slightly incorrect information could drive the group to a better performance.

Item Type: Article
Language: English
Date: December 2017
Refereed: Yes
Place of Publication: Washington, D.C.
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 13 Apr 2018 12:49
Last Modified: 07 Jun 2024 07:41
OAI Identifier: oai:tse-fr.eu:32195
URI: https://publications.ut-capitole.fr/id/eprint/25753
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