Structural analysis and the sum of nodes' betweenness centrality in complex networks

Fuente: arXiv
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Main Authors: Deng, Ronghao, Li, Meizhu, Zhang, Qi
Format: Preprint
Published: 2024
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author Deng, Ronghao
Li, Meizhu
Zhang, Qi
author_facet Deng, Ronghao
Li, Meizhu
Zhang, Qi
contents Structural analysis in network science is finding the information hidden from the topology structure of complex networks. Many methods have already been proposed in the research on the structural analysis of complex networks to find the different structural information of networks. In this work, the sum of nodes' betweenness centrality (SBC) is used as a new structural index to check how the structure of the complex networks changes in the process of the network's growth. We build two four different processes of network growth to check how the structure change will be manifested by the SBC. We find that when the networks are under Barabási-Albert rule, the value of SBC for each network grows like a logarithmic function. However, when the rule that guides the network's growth is the Erdős-Rényi rule, the value of SBC will converge to a fixed value. It means the rules that guide the network's growth can be illustrated by the change of the SBC in the process of the network's growth. In other words, in the structure analysis of complex networks, the sum of nodes' betweenness centrality can be used as an index to check what kinds of rules guide the network's growth.
format Preprint
id arxiv_https___arxiv_org_abs_2402_13507
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Structural analysis and the sum of nodes' betweenness centrality in complex networks
Deng, Ronghao
Li, Meizhu
Zhang, Qi
Physics and Society
Data Analysis, Statistics and Probability
Structural analysis in network science is finding the information hidden from the topology structure of complex networks. Many methods have already been proposed in the research on the structural analysis of complex networks to find the different structural information of networks. In this work, the sum of nodes' betweenness centrality (SBC) is used as a new structural index to check how the structure of the complex networks changes in the process of the network's growth. We build two four different processes of network growth to check how the structure change will be manifested by the SBC. We find that when the networks are under Barabási-Albert rule, the value of SBC for each network grows like a logarithmic function. However, when the rule that guides the network's growth is the Erdős-Rényi rule, the value of SBC will converge to a fixed value. It means the rules that guide the network's growth can be illustrated by the change of the SBC in the process of the network's growth. In other words, in the structure analysis of complex networks, the sum of nodes' betweenness centrality can be used as an index to check what kinds of rules guide the network's growth.
title Structural analysis and the sum of nodes' betweenness centrality in complex networks
topic Physics and Society
Data Analysis, Statistics and Probability
url https://arxiv.org/abs/2402.13507