ID:
publications-4636
Type:
article
Year:
1999
Authors:
BarabΓ΅si, Albert LΓ΅szlΓ³ and BarabΓ΅si, Albert-LΓ΅szlΓ³ and Albert, RΓ©ka and Albert, RΓ©ka and Jeong, Hawoong and Jeong, Hawoong
Title:
Mean-field theory for scale-free random networks
Venue/Journal:
Physica A-statistical Mechanics and Its Applications
DOI:
10.1016/s0378-4371(99)00291-5
Research type:
Water System:
Technical Focus:
Abstract:
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.
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