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Social power and opinion formation in complex networks

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  • Jalili, Mahdi
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    Abstract

    In this paper we investigate the effects of social power on the evolution of opinions in model networks as well as in a number of real social networks. A continuous opinion formation model is considered and the analysis is performed through numerical simulation. Social power is given to a proportion of agents selected either randomly or based on their degrees. As artificial network structures, we consider scale-free networks constructed through preferential attachment and Watts–Strogatz networks. Numerical simulations show that scale-free networks with degree-based social power on the hub nodes have an optimal case where the largest number of the nodes reaches a consensus. However, given power to a random selection of nodes could not improve consensus properties. Introducing social power in Watts–Strogatz networks could not significantly change the consensus profile.

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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 392 (2013)
    Issue (Month): 4 ()
    Pages: 959-966

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    Handle: RePEc:eee:phsmap:v:392:y:2013:i:4:p:959-966

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Complex networks; Social networks; Dynamic opinion formation; Consensus; Social power;

    References

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    1. Diemo Urbig & Jan Lorenz & Heiko Herzberg, 2008. "Opinion Dynamics: the Effect of the Number of Peers Met at Once," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 4.
    2. Kurmyshev, Evguenii & Juárez, Héctor A. & González-Silva, Ricardo A., 2011. "Dynamics of bounded confidence opinion in heterogeneous social networks: Concord against partial antagonism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2945-2955.
    3. A. Szolnoki & M. Perc, 2009. "Promoting cooperation in social dilemmas via simple coevolutionary rules," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, Springer, vol. 67(3), pages 337-344, February.
    4. Mohammad Afshar & Masoud Asadpour, 2010. "Opinion Formation by Informed Agents," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(4), pages 5.
    5. Guillaume Deffuant & Frederic Amblard & G�rard Weisbuch, 2002. "How Can Extremism Prevail? a Study Based on the Relative Agreement Interaction Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(4), pages 1.
    6. Amblard, Frédéric & Deffuant, Guillaume, 2004. "The role of network topology on extremism propagation with the relative agreement opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 725-738.
    7. Gandica, Yérali & del Castillo-Mussot, Marcelo & Vázquez, Gerardo J. & Rojas, Sergio, 2010. "Continuous opinion model in small-world directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5864-5870.
    8. 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 2.
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