A Tractable Complex Network Model based on the Stochastic Mean-field Model of Distance
arXiv:cond-mat/0304701 · doi:10.1007/b98716
Abstract
Much recent research activity has been devoted to empirical study and theoretical models of complex networks (random graphs) with three qualitative features: power-law degree distribution, local clustering of edges, and small diameter. We point out a new (in this context) platform for such models -- the stochastic mean-field model of distance -- and within this platform study a simple two-parameter proportional attachment model. The model is mathematicallly natural, permits a wide variety of explicit calculations, has the desired three qualitative features, and fits the complete range of degree scaling exponents and clustering parameters; in these respects it compares favorably to existing models.
37 pages, 9 figures. Revised version correcting minor mistakes and adding some extra calculations
References in corpus (4)
Cited by in corpus (12)
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