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Information flow in social groups

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Author Info

  • Wu, Fang
  • Huberman, Bernardo A.
  • Adamic, Lada A.
  • Tyler, Joshua R.
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    Abstract

    We present a study of information flow that takes into account the observation that an item relevant to one person is more likely to be of interest to individuals in the same social circle than those outside of it. This is due to the fact that the similarity of node attributes in social networks decreases as a function of the graph distance. An epidemic model on a scale-free network with this property has a finite threshold, implying that the spread of information is limited. We tested our predictions by measuring the spread of messages in an organization and also by numerical experiments that take into consideration the organizational distance among individuals.

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    Bibliographic Info

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

    Volume (Year): 337 (2004)
    Issue (Month): 1 ()
    Pages: 327-335

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    Handle: RePEc:eee:phsmap:v:337:y:2004:i:1:p:327-335

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

    Related research

    Keywords: Epidemics; Scale-free networks; Information flow;

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    Cited by:
    1. Deffuant, Guillaume & Huet, Sylvie, 2007. "Propagation effects of filtering incongruent information," Journal of Business Research, Elsevier, vol. 60(8), pages 816-825, August.
    2. Chen, Yenming & Wu, Tien-Hua, 2010. "The diffusion dynamics of the informal sector and sustainable WEEE supply chain," MPRA Paper 25650, University Library of Munich, Germany.
    3. Roth, Camille, 2007. "Empiricism for descriptive social network models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(1), pages 53-58.
    4. Ozsoylev, Han N. & Walden, Johan, 2011. "Asset pricing in large information networks," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2252-2280.
    5. Santiago, A. & Benito, R.M., 2008. "Connectivity degrees in the threshold preferential attachment model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(10), pages 2365-2376.
    6. Guimera, R. & Danon, L. & Diaz-Guilera, A. & Giralt, F. & Arenas, A., 2006. "The real communication network behind the formal chart: Community structure in organizations," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 653-667, December.

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