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Opinion Dynamics under Conformity

  • Berno Buechel

    (University of Hamburg)

  • Tim Hellmann

    (Institute of Mathematical Economics)

  • Stefan Kloessner

    (Saarland University)

We present a model of opinion formation where individuals repeatedly engage in discussion and update their opinion in a social network similarly to the DeGroot model. Abstracting from the standard assumption that individuals always report their opinion truthfully, agents in our model interact strategically in the discussion such that their stated opinion can di er from their true opinion. The incentive to do so is induced by agents' preferences for conformity. Highly conforming agents will state an opinion which is close to their neighbors' while agents with low level of conformity may be honest or even overstate their opinion. We model opinion formation as a dynamic process and identify conditions for convergence to consensus. Studying the consensus in detail, we show that an agent's social in uence on the consensus opinion is increasing in network centrality and decreasing in the level of conformity. Thus, lower conformity fosters opinion leadership. Moreover, assuming that the initial opinion is a noisy signal about some true state of the world, we consider the mean squared error of the consensus as an estimator for the true state of the world. We show that a society is \wise", i.e. the mean squared error is smaller, if players who are well informed are less conform, while uninformed players conform more with their neighbors.

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File URL: http://www.imw.uni-bielefeld.de/n/upload/paper/757b505cfd34c64c85ca5b5690ee5293.pdf
File Function: First version, 2012
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Paper provided by Bielefeld University, Center for Mathematical Economics in its series Working Papers with number 469.

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Length: 36 pages
Date of creation: Jul 2012
Date of revision:
Handle: RePEc:bie:wpaper:469
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  1. Allison, G. & Fudenberg, D., 1992. "Rules of Thumb for Social Learning," Working papers 92-12, Massachusetts Institute of Technology (MIT), Department of Economics.
  2. Ariely, Dan & Levav, Jonathan, 2000. " Sequential Choice in Group Settings: Taking the Road Less Traveled and Less Enjoyed," Journal of Consumer Research, University of Chicago Press, vol. 27(3), pages 279-90, December.
  3. Andrea Galeotti & Sanjeev Goyal, 2007. "A Theory of Strategic Diffusion," Economics Discussion Papers 635, University of Essex, Department of Economics.
  4. Hayakawa, Hiroaki & Venieris, Yiannis P, 1977. "Consumer Interdependence via Reference Groups," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 599-615, June.
  5. 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.
  6. Buechel, Berno & Hellmann, Tim & Pichler, Michael M., 2014. "The dynamics of continuous cultural traits in social networks," Journal of Economic Theory, Elsevier, vol. 154(C), pages 274-309.
  7. Fudenberg, Drew & Ellison, Glenn, 1995. "Word-of-Mouth Communication and Social Learning," Scholarly Articles 3196300, Harvard University Department of Economics.
  8. Lorenz, Jan, 2005. "A stabilization theorem for dynamics of continuous opinions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 217-223.
  9. Bernheim, B Douglas, 1994. "A Theory of Conformity," Journal of Political Economy, University of Chicago Press, vol. 102(5), pages 841-77, October.
  10. Bala, V. & Goyal, S., 1995. "Learning from Neighbors," Econometric Institute Research Papers EI 9549-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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