On the Distributions of Subgraph Centralities in Complex Networks

Subgraph centrality measure characterizes the participation of each node in all subgraphs in a network. Smaller subgraphs are given more weight than large ones, which makes this measure appropriate for characterizing network motifs. This measure is better in being able to discriminate the nodes of a...

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Bibliographic Details
Published in:Discrete Dynamics in Nature and Society 2013-01, Vol.2013 (2013), p.105-112-113
Main Authors: Li, Faxu, Wei, Liang, Zhao, Haixing, Hu, Feng
Format: Article
Language:English
Subjects:
Complex systems
Computer simulation
Distribution (Probability theory)
Graph theory
Mathematical research
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Summary:Subgraph centrality measure characterizes the participation of each node in all subgraphs in a network. Smaller subgraphs are given more weight than large ones, which makes this measure appropriate for characterizing network motifs. This measure is better in being able to discriminate the nodes of a network than alternate measures. In this paper, the important issue of subgraph centrality distributions is investigated through theory-guided extensive numerical simulations, for three typical complex network models, namely, the ER random-graph networks, WS small-world networks, and BA scale-free networks. It is found that these three very different types of complex networks share some common features, particularly that the subgraph centrality distributions in increasing order are all insensitive to the network connectivity characteristics, and also found that the probability distributions of subgraph centrality of the ER and of the WS models both follow the gamma distribution, and the BA scale-free networks exhibit a power-law distribution with an exponential cutoff.
ISSN:1026-0226
1607-887X
DOI:10.1155/2013/473248