Spatial Correlation Function in Modular Networks

Spatial Correlation Function in Modular Networks

Year:    2008

Communications in Computational Physics, Vol. 3 (2008), Iss. 3 : pp. 724–733

Abstract

Due to the complexity of the interactions among the nodes of the complex networks, the properties of the network modules, to a large extent, remain unknown or unexplored. In this paper, we introduce the spatial correlation function Grs to describe the correlations among the modules of the weighted networks. In order to test the proposed method, we use our method to analyze and discuss the modular structures of the ER random networks, scale-free networks and the Chinese railway network. Rigorous analysis of the existing data shows that the spatial correlation function Grs is suitable for describing the correlations among different network modules. Remarkably, we find that different networks display different correlations, especially, the correlation function Grs with different networks meets different degree distribution, such as the linear and exponential distributions.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2008-CiCP-7872

Communications in Computational Physics, Vol. 3 (2008), Iss. 3 : pp. 724–733

Published online:    2008-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    10

Keywords: