IDEAS home Printed from https://ideas.repec.org/p/tse/wpaper/124257.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.tse-fr.eu/sites/default/files/TSE/documents/doc/wp/2020/wp_tse_1101.pdf
    File Function: Full Text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bertrand Jayles & Ramon Escobedo & Stéphane Cezera & Adrien Blanchet & Tatsuya Kameda & Clément Sire & Guy Théraulaz, 2020. "The impact of incorrect social information on collective wisdom in human groups," Post-Print hal-03019820, HAL.
    2. 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.
    3. 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.
    4. Shane T. Mueller & Yin-Yin Sarah Tan, 2018. "Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization," Journal of Computational Social Science, Springer, vol. 1(1), pages 15-48, January.
    5. Marcella Tambuscio & Diego F. M. Oliveira & Giovanni Luca Ciampaglia & Giancarlo Ruffo, 2018. "Network segregation in a model of misinformation and fact-checking," Journal of Computational Social Science, Springer, vol. 1(2), pages 261-275, September.
    6. Kathie M. d'I. Treen & Hywel T. P. Williams & Saffron J. O'Neill, 2020. "Online misinformation about climate change," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(5), September.
    7. Peng Cheng & Zhe Ouyang & Yang Liu, 0. "The effect of information overload on the intention of consumers to adopt electric vehicles," Transportation, Springer, vol. 0, pages 1-20.
    8. Casey A. Klofstad & Joseph E. Uscinski & Jennifer M. Connolly & Jonathan P. West, 2019. "What drives people to believe in Zika conspiracy theories?," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-8, December.
    9. Jascha-Alexander Koch & Michael Siering, 2019. "The recipe of successful crowdfunding campaigns," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(4), pages 661-679, December.
    10. García, V.J. & Gómez-Déniz, E. & Vázquez-Polo, F.J., 2010. "A new skew generalization of the normal distribution: Properties and applications," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 2021-2034, August.
    11. Lori Beaman & Ariel BenYishay & Jeremy Magruder & Ahmed Mushfiq Mobarak, 2021. "Can Network Theory-Based Targeting Increase Technology Adoption?," American Economic Review, American Economic Association, vol. 111(6), pages 1918-1943, June.
    12. Carlos Carrasco-Farré, 2022. "The fingerprints of misinformation: how deceptive content differs from reliable sources in terms of cognitive effort and appeal to emotions," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-18, December.
    13. Stocks, Morris H. & Harrell, Adrian, 1995. "The impact of an increase in accounting information level on the judgment quality of individuals and groups," Accounting, Organizations and Society, Elsevier, vol. 20(7-8), pages 685-700.
    14. Germano, Fabrizio & Sobbrio, Francesco, 2020. "Opinion dynamics via search engines (and other algorithmic gatekeepers)," Journal of Public Economics, Elsevier, vol. 187(C).
    15. Tianchang Ni & Runping Zhu & Richard Krever, 2023. "Responses to News Overload in a Non-Partisan Environment: News Avoidance in China," SAGE Open, , vol. 13(3), pages 21582440231, July.
    16. Tomi Rajala, 2019. "Mind the Information Expectation Gap," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(1), pages 104-125, March.
    17. Ashill, Nicholas J. & Rod, Michel, 2011. "Burnout processes in non-clinical health service encounters," Journal of Business Research, Elsevier, vol. 64(10), pages 1116-1127, October.
    18. Hurley, Patrick J., 2015. "Ego depletion: Applications and implications for auditing research," Journal of Accounting Literature, Elsevier, vol. 35(C), pages 47-76.
    19. Yiangos Papanastasiou, 2020. "Fake News Propagation and Detection: A Sequential Model," Management Science, INFORMS, vol. 66(5), pages 1826-1846, May.
    20. Nie, Yanyi & Li, Wenyao & Pan, Liming & Lin, Tao & Wang, Wei, 2022. "Markovian approach to tackle competing pathogens in simplicial complex," Applied Mathematics and Computation, Elsevier, vol. 417(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tse:wpaper:124257. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/tsetofr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.