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Spread of (mis)information in social networks

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Author Info

  • 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.

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Bibliographic Info

Article provided by Elsevier in its journal Games and Economic Behavior.

Volume (Year): 70 (2010)
Issue (Month): 2 (November)
Pages: 194-227

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Handle: RePEc:eee:gamebe:v:70:y:2010:i:2:p:194-227

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Web page: http://www.elsevier.com/locate/inca/622836

Related research

Keywords: Information aggregation Learning Misinformation Social networks;

References

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  1. Jeanne Hagenbach & Frédéric Koessler, 2010. "Strategic Communication Networks," Review of Economic Studies, Oxford University Press, vol. 77(3), pages 1072-1099.
  2. Farrell, Joseph & Gibbons, Robert, 1989. "Cheap Talk with Two Audiences," American Economic Review, American Economic Association, vol. 79(5), pages 1214-23, December.
  3. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
  4. Crawford, Vincent P & Sobel, Joel, 1982. "Strategic Information Transmission," Econometrica, Econometric Society, vol. 50(6), pages 1431-51, November.
  5. Celen, Bogachan & Kariv, Shachar, 2004. "Observational learning under imperfect information," Games and Economic Behavior, Elsevier, vol. 47(1), pages 72-86, April.
  6. repec:fth:stanho:e-89-7 is not listed on IDEAS
  7. Daron Acemoglu & Munther A. Dahleh & Ilan Lobel & Asuman Ozdaglar, 2008. "Bayesian Learning in Social Networks," NBER Working Papers 14040, National Bureau of Economic Research, Inc.
  8. Bala, Venkatesh & Goyal, Sanjeev, 1998. "Learning from Neighbours," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 595-621, July.
  9. Bogaçhan Çelen & Shachar Kariv, 2004. "Distinguishing Informational Cascades from Herd Behavior in the Laboratory," American Economic Review, American Economic Association, vol. 94(3), pages 484-498, June.
  10. Ambrus, Attila & Takahashi, Satoru, 2008. "Multi-sender cheap talk with restricted state spaces," Theoretical Economics, Econometric Society, vol. 3(1), March.
  11. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 2010. "A theory of Fads, Fashion, Custom and cultural change as informational Cascades," Levine's Working Paper Archive 1193, David K. Levine.
  12. Peter M. Demarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion Bias, Social Influence, And Unidimensional Opinions," The Quarterly Journal of Economics, MIT Press, vol. 118(3), pages 909-968, August.
  13. Smith, L. & Sorensen, P., 1996. "Pathological Outcomes of Observational Learning," Working papers 96-19, Massachusetts Institute of Technology (MIT), Department of Economics.
  14. Abhijit Banerjee & Drew Fudenberg, 2010. "Word of Mouth Learning," Levine's Working Paper Archive 723, David K. Levine.
  15. Banerjee, Abhijit V, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, MIT Press, vol. 107(3), pages 797-817, August.
  16. Andrea Galeotti & Christian Ghiglino & Francesco Squintani, 2009. "Strategic Information Transmission in Networks," Economics Discussion Papers 668, University of Essex, Department of Economics.
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Citations

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Cited by:
  1. Berno Buechel & Tim Hellmann & Stefan Kloessner, 2012. "Opinion Dynamics under Conformity," Working Papers 469, Bielefeld University, Center for Mathematical Economics.
  2. 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.
  3. Mueller-Frank, Manuel, 2013. "A general framework for rational learning in social networks," Theoretical Economics, Econometric Society, vol. 8(1), January.
  4. Manuel Förster & Ana Mauleon & Vincent Vannetelbosch, 2013. "Trust and Manipulation in Social Networks," Documents de travail du Centre d'Economie de la Sorbonne 13065, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  5. Carlos Lever Guzmán, 2010. "Strategic Spending in Voting Competitions with Social Networks," Working Papers 2010-16, Banco de México.
  6. Yang Lu & Wing Suen & Heng Chen, 2013. "The Power of Whispers: A Theory of Rumor, Communication and Revolution," 2013 Meeting Papers 411, Society for Economic Dynamics.

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