Information flow in social groups
AbstractWe 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 InfoArticle provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.
Volume (Year): 337 (2004)
Issue (Month): 1 ()
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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/
Epidemics; Scale-free networks; Information flow;
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- 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.
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- 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.
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