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Dynamics of Opinion Forming in Structurally Balanced Social Networks

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  • Claudio Altafini

Abstract

A structurally balanced social network is a social community that splits into two antagonistic factions (typical example being a two-party political system). The process of opinion forming on such a community is most often highly predictable, with polarized opinions reflecting the bipartition of the network. The aim of this paper is to suggest a class of dynamical systems, called monotone systems, as natural models for the dynamics of opinion forming on structurally balanced social networks. The high predictability of the outcome of a decision process is explained in terms of the order-preserving character of the solutions of this class of dynamical systems. If we represent a social network as a signed graph in which individuals are the nodes and the signs of the edges represent friendly or hostile relationships, then the property of structural balance corresponds to the social community being splittable into two antagonistic factions, each containing only friends.

Suggested Citation

  • Claudio Altafini, 2012. "Dynamics of Opinion Forming in Structurally Balanced Social Networks," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-9, June.
  • Handle: RePEc:plo:pone00:0038135
    DOI: 10.1371/journal.pone.0038135
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    References listed on IDEAS

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    1. Axelrod, Robert & Bennett, D. Scott, 1993. "A Landscape Theory of Aggregation," British Journal of Political Science, Cambridge University Press, vol. 23(2), pages 211-233, April.
    2. Robert Axelrod & Will Mitchell & Robert E. Thomas & D. Scott Bennett & Erhard Bruderer, 1995. "Coalition Formation in Standard-Setting Alliances," Management Science, INFORMS, vol. 41(9), pages 1493-1508, September.
    3. Galam, Serge, 1996. "Fragmentation versus stability in bimodal coalitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 230(1), pages 174-188.
    4. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
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    Cited by:

    1. Christian Bongiorno & Damien Challet, 2019. "Nonparametric sign prediction of high-dimensional correlation matrix coefficients," Working Papers hal-02335586, HAL.
    2. Sheykhali, Somaye & Darooneh, Amir Hossein & Jafari, Gholam Reza, 2020. "Partial balance in social networks with stubborn links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).

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