Mean-field theory for scale-free random networks

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Random networks with complex topology are common in Nature, describing systems as diverse as the world wide web or social and business networks. Recently, it has been demonstrated that most large networks for which topological information is available display scale-free features. Here we study the scaling properties of the recently introduced scale-free model, that can account for the observed power-law distribution of the connectivities. We develop a mean-field method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the scaling exponents. The mean-field method can be used to address the properties of two variants of the scale-free model, that do not display power-law scaling. (C) 1999 Elsevier Science B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
1999-10
Language
English
Article Type
Article
Keywords

SMALL-WORLD NETWORKS

Citation

PHYSICA A, v.272, no.1-2, pp.173 - 187

ISSN
0378-4371
DOI
10.1016/S0378-4371(99)00291-5
URI
http://hdl.handle.net/10203/75969
Appears in Collection
PH-Journal Papers(저널논문)
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