A Tractable Complex Network Model based on the Stochastic Mean-field Model of Distance

Physics – Condensed Matter – Disordered Systems and Neural Networks

Scientific paper

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37 pages, 9 figures. Revised version correcting minor mistakes and adding some extra calculations

Scientific paper

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.

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