Random networks with given rich-club coefficient

In complex networks it is common to model a network or generate a surrogate network based on the conservation of the number of connections of individual nodes. In this paper we analyse the ensemble of random networks that are defined by the conservation of the rich-club coefficient, which measures t...

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Bibliographic Details
Published inThe European physical journal. B, Condensed matter physics Vol. 85; no. 9
Main Authors Mondragón, R. J., Zhou, S.
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer-Verlag 01.09.2012
EDP Sciences
Springer
Subjects
Complex Systems
Computational methods in statistical physics and nonlinear dynamics
Condensed Matter Physics
Exact sciences and technology
Fluid- and Aerodynamics
Physics
Physics and Astronomy
Regular Article
Solid State Physics
Statistical physics, thermodynamics, and nonlinear dynamical systems
Stochastic analysis methods (fokker-planck, langevin, etc.)
Statistical and Nonlinear Physics
Stochastic model
Algorithms
Statistical analysis
Complex system
Nodes
Distribution functions
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Summary:In complex networks it is common to model a network or generate a surrogate network based on the conservation of the number of connections of individual nodes. In this paper we analyse the ensemble of random networks that are defined by the conservation of the rich-club coefficient, which measures the density of connections among a group of nodes. We also present a method to generate such surrogate networks for a given network. We show that by choosing a suitable local linking term, the random networks not only preserve the rich-club coefficient but also closely approximate the degree distribution and the mixing pattern of real networks. Our work provides a different and complementary perspective to the network randomisation problem.
ISSN:1434-6028
1434-6036
DOI:10.1140/epjb/e2012-21026-3