Normalized entropy of rank distribution: a novel measure of heterogeneity of complex networks

Autor:	Zhu Da-zhi, Wu Jun, Tan Yue-jin, Deng Hong-zhong
Rok vydání:	2007
Předmět:	Computer science Nerd Exponent General Physics and Astronomy Entropy (information theory) Statistical physics Complex network Scaling Statistic
Zdroj:	ResearcherID
ISSN:	1741-4199 1009-1963
Popis:	Many unique properties of complex networks result from heterogeneity. The measure and analysis of heterogeneity are important and desirable to the research of the properties and functions of complex networks. In this paper, the rank distribution is proposed as a new statistic feature of complex networks. Based on the rank distribution, a novel measure of the heterogeneity called a normalized entropy of rank distribution (NERD) is proposed. The NERD accords with the normal meaning of heterogeneity within the context of complex networks compared with conventional measures. The heterogeneity of scale-free networks is studied using the NERD. It is shown that scale-free networks become more heterogeneous as the scaling exponent decreases and the NERD of scale-free networks is independent of the number of vertices, which indicates that the NERD is a suitable and effective measure of heterogeneity for networks with different sizes.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::afafee7b34b132588ba441d7db8d6ab9 https://doi.org/10.1088/1009-1963/16/6/014 Zobrazit plný text záznamu