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Consensus in Social Networks: Revisited

Author

Listed:
  • Steven Kivinen
  • Norovsambuu Tumennasan

    (Department of Economics, Dalhousie University)

Abstract

We analyze the convergence of opinions or beliefs in a general social network with non-Bayesian agents. We provide a new sufficient condition under which opinions converge to consensus. Our condition is significantly more permissive than that of Lorenz (2005).

Suggested Citation

  • Steven Kivinen & Norovsambuu Tumennasan, 2016. "Consensus in Social Networks: Revisited," Working Papers daleconwp2016-05, Dalhousie University, Department of Economics.
    • Handle: RePEc:dal:wpaper:daleconwp2016-05
    as

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    File URL: http://wp.economics.dal.ca/RePEc/dal/wpaper/DalEconWP2016-05.pdf
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    References listed on IDEAS

    as
    1. Kivinen, Steven, 2017. "Polarization in strategic networks," Economics Letters, Elsevier, vol. 154(C), pages 81-83.
    2. Mueller-Frank, Manuel, 2014. "Does one Bayesian make a difference?," Journal of Economic Theory, Elsevier, vol. 154(C), pages 423-452.
    3. Pooya Molavi & Alireza Tahbaz‐Salehi & Ali Jadbabaie, 2018. "A Theory of Non‐Bayesian Social Learning," Econometrica, Econometric Society, vol. 86(2), pages 445-490, March.
    4. Peter M. DeMarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion Bias, Social Influence, and Unidimensional Opinions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(3), pages 909-968.
    5. Geanakoplos, John D. & Polemarchakis, Heraklis M., 1982. "We can't disagree forever," Journal of Economic Theory, Elsevier, vol. 28(1), pages 192-200, October.
    6. 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.
    7. Mueller-Frank, Manuel, 2015. "Reaching Consensus in Social Networks," IESE Research Papers D/1116, IESE Business School.
    Full references (including those not matched with items on IDEAS)

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    Keywords

    Networks; Consensus; Learning;
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