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The impact of incorrect social information on collective wisdom in human groups

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  • Jayles, Bertrand
  • Escobedo, Ramon
  • Cezera, Stéphane
  • Blanchet, Adrien
  • Kameda, Tatsuya
  • Sire, Clément
  • Théraulaz, Guy

Abstract

A major problem that resulted from the massive use of social media networks is the diffusion of incorrect information. However, very few studies have investigated the impact of incorrect information on individual and collective decisions. We performed experiments in which participants had to estimate a series of quantities before and after receiving social information. Unbeknownst to them, we controlled the degree of inaccuracy of the social information through "virtual influencers", who provided some incorrect information. We find that a large proportion of individuals only partially follow the social information, thus resisting incorrect information. Moreover, we find that incorrect social information can help a group perform better when it overestimates the true value, by partly compensating a human underestimation bias. Overall, our results suggest that incorrect information does not necessarily impair the collective wisdom of groups, and can even be used to dampen the negative effects of known cognitive biases.

Suggested Citation

  • Jayles, Bertrand & Escobedo, Ramon & Cezera, Stéphane & Blanchet, Adrien & Kameda, Tatsuya & Sire, Clément & Théraulaz, Guy, 2020. "The impact of incorrect social information on collective wisdom in human groups," TSE Working Papers 1101, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:124257
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    References listed on IDEAS

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    1. Schick, Allen G. & Gordon, Lawrence A. & Haka, Susan, 1990. "Information overload: A temporal approach," Accounting, Organizations and Society, Elsevier, vol. 15(3), pages 199-220.
    2. Alessandro Bessi & Mauro Coletto & George Alexandru Davidescu & Antonio Scala & Guido Caldarelli & Walter Quattrociocchi, 2015. "Science vs Conspiracy: Collective Narratives in the Age of Misinformation," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-17, February.
    3. Andrés Chacoma & Damián H Zanette, 2015. "Opinion Formation by Social Influence: From Experiments to Modeling," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-16, October.
    4. Gabriel Madirolas & Gonzalo G de Polavieja, 2015. "Improving Collective Estimations Using Resistance to Social Influence," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-16, November.
    5. Pavlin Mavrodiev & Claudio J. Tessone & Frank Schweitzer, "undated". "Quantifying the effects of social influence," Working Papers ETH-RC-13-001, ETH Zurich, Chair of Systems Design.
    6. Corentin Vande Kerckhove & Samuel Martin & Pascal Gend & Peter J Rentfrow & Julien M Hendrickx & Vincent D Blondel, 2016. "Modelling Influence and Opinion Evolution in Online Collective Behaviour," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-25, June.
    7. Saralees Nadarajah, 2005. "A generalized normal distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(7), pages 685-694.
    8. Xiaoyan Qiu & Diego F. M. Oliveira & Alireza Sahami Shirazi & Alessandro Flammini & Filippo Menczer, 2017. "Limited individual attention and online virality of low-quality information," Nature Human Behaviour, Nature, vol. 1(7), pages 1-7, July.
    9. Bjarke Mønsted & Piotr Sapieżyński & Emilio Ferrara & Sune Lehmann, 2017. "Evidence of complex contagion of information in social media: An experiment using Twitter bots," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-12, September.
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    1. Bertrand Jayles & Clément Sire & Ralf H J M Kurvers, 2021. "Crowd control: Reducing individual estimation bias by sharing biased social information," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-28, November.

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