Symmetry-based structure entropy of complex networks

Yang-Hua Xiao, Wen-Tao Wu, Hui Wang, Momiao Xiong and Wei Wang

Physica A: Statistical Mechanics and its Applications, 2008, vol. 387, issue 11, 2611-2619

Abstract: Precisely quantifying the heterogeneity or disorder of network systems is important and desired in studies of behaviors and functions of network systems. Although various degree-based entropies have been available to measure the heterogeneity of real networks, heterogeneity implicated in the structures of networks can not be precisely quantified yet. Hence, we propose a new structure entropy based on automorphism partition. Analysis of extreme cases shows that entropy based on automorphism partition can quantify the structural heterogeneity of networks more precisely than degree-based entropies. We also summarized symmetry and heterogeneity statistics of many real networks, finding that real networks are more heterogeneous in the view of automorphism partition than what have been depicted under the measurement of degree-based entropies; and that structural heterogeneity is strongly negatively correlated to symmetry of real networks.

Keywords: Structure entropy; Symmetry; Complex network (search for similar items in EconPapers)
Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:387:y:2008:i:11:p:2611-2619

DOI: 10.1016/j.physa.2008.01.027

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