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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. V. Crawford & J. Sobel, 2010. "Strategic Information Transmission," Levine's Working Paper Archive 544, David K. Levine.
  2. Farrell, J. & Gibbons, R., 1989. "Cheap Talk With Two Audiences," Working papers 518, Massachusetts Institute of Technology (MIT), Department of Economics.
  3. Ambrus, Attila & Takahashi, Satoru, 2008. "Multi-sender cheap talk with restricted state spaces," Theoretical Economics, Econometric Society, vol. 3(1), March.
  4. 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.
  5. Banerjee, Abhijit V, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, MIT Press, vol. 107(3), pages 797-817, August.
  6. Celen, Bogachan & Kariv, Shachar, 2004. "Observational learning under imperfect information," Games and Economic Behavior, Elsevier, vol. 47(1), pages 72-86, April.
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  8. Jeanne Hagenbach & Frédéric Koessler, 2008. "Strategic communication networks," PSE Working Papers halshs-00586847, HAL.
  9. Lones Smith & Peter Sorensen, 2000. "Pathological Outcomes of Observational Learning," Econometrica, Econometric Society, vol. 68(2), pages 371-398, March.
  10. Zwiebel, Jeffrey H. & Vayanos, Dimitri & DeMarzo, Peter M., 2001. "Persuasion Bias, Social Influence, and Uni-Dimensional Opinions," Research Papers 1719, Stanford University, Graduate School of Business.
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  12. Banerjee, Abhijit & Fudenberg, Drew, 2004. "Word-of-mouth learning," Games and Economic Behavior, Elsevier, vol. 46(1), pages 1-22, January.
  13. Andrea Galeotti & Christian Ghiglino & Francesco Squintani, 2009. "Strategic Information Transmission in Networks," Economics Discussion Papers 668, University of Essex, Department of Economics.
  14. 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.
  15. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
  16. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
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Citations

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Cited by:
  1. Carlos Lever Guzmán, 2010. "Strategic Spending in Voting Competitions with Social Networks," Working Papers 2010-16, Banco de México.
  2. Mueller-Frank, Manuel, 2013. "A general framework for rational learning in social networks," Theoretical Economics, Econometric Society, vol. 8(1), January.
  3. 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.
  4. Büchel, Berno & Hellmann, Tim & Klößner, Stefan, 2013. "Opinion Dynamics and Wisdom under Conformity," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79770, Verein für Socialpolitik / German Economic Association.
  5. Manuel Förster & Ana Mauleon & Vincent J. Vannetelbosch, 2014. "Trust and Manipulation in Social Networks," Working Papers 2014.50, Fondazione Eni Enrico Mattei.
  6. 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.

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