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Influence networks

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  • López-Pintado, Dunia
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    Abstract

    Some behaviors, ideas or technologies spread and become persistent in society, whereas others vanish. This paper analyzes the role of social influence in determining such distinct collective outcomes. Agents are assumed to acquire information from others through a certain sampling process, that generates an influence network, and they use simple rules to decide whether to adopt or not depending on the behavior of the observed sample. We characterize, as a function of the primitives of the model, the diffusion threshold (i.e., the spreading rate above which the adoption of the new behavior becomes persistent in the population) and the endemic state (i.e., the fraction of adopters in the stationary state of the dynamics). We find that an increase in the correlation between the out-degree (information level) and in-degree (visibility level) of agents may favor or harm diffusion; the effect actually depends on the specific details of the adoption process.

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    Bibliographic Info

    Article provided by Elsevier in its journal Games and Economic Behavior.

    Volume (Year): 75 (2012)
    Issue (Month): 2 ()
    Pages: 776-787

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    Handle: RePEc:eee:gamebe:v:75:y:2012:i:2:p:776-787

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    Web page: http://www.elsevier.com/locate/inca/622836

    Related research

    Keywords: Social influence; Networks; Diffusion threshold; Endemic state;

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    1. Bramoulle, Yann & Kranton, Rachel, 2007. "Public goods in networks," Journal of Economic Theory, Elsevier, vol. 135(1), pages 478-494, July.
    2. Benaim, Michel & Weibull, Jörgen W., 2000. "Deterministic Approximation of Stochastic Evolution in Games," Working Paper Series 534, Research Institute of Industrial Economics, revised 30 Oct 2001.
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    4. Dunia López-Pintado, 2006. "Contagion and coordination in random networks," International Journal of Game Theory, Springer, vol. 34(3), pages 371-381, October.
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    12. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, University of Chicago Press, vol. 34(4), pages 441-458, 05.
    13. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
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