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The 3-cycle weighted spectral distribution in evolving community-based networks.

作者信息

Jiao Bo, Wu Xiaoqun

机构信息

Luoyang Electronic Equipment Test Center, Luoyang 471003, China.

School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China.

出版信息

Chaos. 2017 Mar;27(3):033109. doi: 10.1063/1.4978024.

Abstract

One of the main organizing principles in real-world networks is that of network communities, where sets of nodes organize into densely linked clusters. Many of these community-based networks evolve over time, that is, we need some size-independent metrics to capture the connection relationships embedded in these clusters. One of these metrics is the average clustering coefficient, which represents the triangle relationships between all nodes of networks. However, the vast majority of network communities is composed of low-degree nodes. Thus, we should further investigate other size-independent metrics to subtly measure the triangle relationships between low-degree nodes. In this paper, we study the 3-cycle weighted spectral distribution (WSD) defined as the weighted sum of the normalized Laplacian spectral distribution with a scaling factor n, where n is the network size (i.e., the node number). Using some diachronic community-based network models and real-world networks, we demonstrate that the ratio of the 3-cycle WSD to the network size is asymptotically independent of the network size and strictly represents the triangle relationships between low-degree nodes. Additionally, we find that the ratio is a good indicator of the average clustering coefficient in evolving community-based systems.

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