Structural analysis and the sum of nodes' betweenness centrality in complex networks
Abstract
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.
Authors 3
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Jiangsu University of Science and Technology
Affiliation as printed
School of Science , Jiangsu University of Science and Technology , Zhenjiang 212100 , China
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Affiliation as printed
School of Computer Science and Communication Engineering , Jiangsu University , Zhenjiang , Jiangsu , China
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Leiden University · Jiangsu University of Science and Technology · Lorentz Center
Affiliation as printed
Lorentz Institute for Theoretical Physics , Leiden University , PO Box 9504 , 2300 RA Leiden , The Netherlands
School of Science , Jiangsu University of Science and Technology , Zhenjiang 212100 , China
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