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Spread of (mis)information in social networks

Author

Listed:
  • Acemoglu, Daron
  • Ozdaglar, Asuman
  • ParandehGheibi, Ali

Abstract

We provide a model to investigate the tension between information aggregation and spread of misinformation. Individuals meet pairwise and exchange information, which is modeled as both individuals adopting the average of their pre-meeting beliefs. "Forceful" agents influence the beliefs of (some of) the other individuals they meet, but do not change their own opinions. We characterize how the presence of forceful agents interferes with information aggregation. Under the assumption that even forceful agents obtain some information from others, we first show that all beliefs converge to a stochastic consensus. Our main results quantify the extent of misinformation by providing bounds or exact results on the gap between the consensus value and the benchmark without forceful agents (where there is efficient information aggregation). The worst outcomes obtain when there are several forceful agents who update their beliefs only on the basis of information from individuals that have been influenced by them.

Suggested Citation

  • Acemoglu, Daron & Ozdaglar, Asuman & ParandehGheibi, Ali, 2010. "Spread of (mis)information in social networks," Games and Economic Behavior, Elsevier, vol. 70(2), pages 194-227, November.
  • Handle: RePEc:eee:gamebe:v:70:y:2010:i:2:p:194-227
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Arifovic, Jasmina & Eaton, B. Curtis & Walker, Graeme, 2015. "The coevolution of beliefs and networks," Journal of Economic Behavior & Organization, Elsevier, vol. 120(C), pages 46-63.
    2. Förster, Manuel & Mauleon, Ana & Vannetelbosch, Vincent J., 2016. "Trust and manipulation in social networks," Network Science, Cambridge University Press, vol. 4(02), pages 216-243, June.
    3. Syngjoo Choi & Edoardo Gallo & Shachar Kariv, 2015. "Networks in the laboratory," Cambridge Working Papers in Economics 1551, Faculty of Economics, University of Cambridge.
    4. Jadbabaie, Ali & Molavi, Pooya & Sandroni, Alvaro & Tahbaz-Salehi, Alireza, 2012. "Non-Bayesian social learning," Games and Economic Behavior, Elsevier, vol. 76(1), pages 210-225.
    5. Heng Chen & Yang K. Lu & Wing Suen, 2016. "The Power Of Whispers: A Theory Of Rumor, Communication, And Revolution," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57, pages 89-116, February.
    6. Christoph Aymanns & Jakob Foerster & Co-Pierre Georg, 2017. "Fake News in Social Networks," Papers 1708.06233, arXiv.org.
    7. Bertin Martens & Luis Aguiar & Estrella Gomez Herrera & Frank Muller, 2018. "The digital transformation of news media and the rise of disinformation and fake news," JRC Working Papers on Digital Economy 2018-02, Joint Research Centre (Seville site).
    8. Eger, Steffen, 2016. "Opinion dynamics and wisdom under out-group discrimination," Mathematical Social Sciences, Elsevier, vol. 80(C), pages 97-107.
    9. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    10. Prummer, Anja & Siedlarek, Jan-Peter, 2017. "Community leaders and the preservation of cultural traits," Journal of Economic Theory, Elsevier, vol. 168(C), pages 143-176.
    11. Bindel, David & Kleinberg, Jon & Oren, Sigal, 2015. "How bad is forming your own opinion?," Games and Economic Behavior, Elsevier, vol. 92(C), pages 248-265.
    12. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska & Emily Tanimura, 2015. "Strategic influence in social networks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01158168, HAL.
    13. Mueller-Frank, Manuel, 2014. "Does one Bayesian make a difference?," Journal of Economic Theory, Elsevier, vol. 154(C), pages 423-452.
    14. Zhao, Jiuhua & Liu, Qipeng & Wang, Lin & Wang, Xiaofan, 2017. "Competitive seeds-selection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 240-248.
    15. Carlos Lever Guzmán, 2010. "Strategic Spending in Voting Competitions with Social Networks," Working Papers 2010-16, Banco de México.
    16. repec:eee:jeborg:v:149:y:2018:i:c:p:46-57 is not listed on IDEAS
    17. Christoph Aymanns & Jakob Foerster & Co-Pierre Georg, 2017. "Fake News in Social Networks," Working Papers on Finance 1804, University of St. Gallen, School of Finance.
    18. repec:the:publsh:3056 is not listed on IDEAS
    19. Mueller-Frank, Manuel, 2013. "A general framework for rational learning in social networks," Theoretical Economics, Econometric Society, vol. 8(1), January.
    20. Gallo, Edoardo, 2014. "Social learning by chit-chat," Journal of Economic Theory, Elsevier, vol. 153(C), pages 313-343.
    21. Fang, Aili & Wang, Lin & Zhao, Jiuhua & Wang, Xiaofan, 2013. "Chaos in social learning with multiple true states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5786-5792.

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