A New Method for Extracting the Hierarchical Organization of Networks

Weihua Zhan, Jihong Guan () and Zhongzhi Zhang ()
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Weihua Zhan: College of Information Science and Engineering, Ningbo University, Ningbo 315211, China†Department of Computer Science and Technology, Tongji University, Shanghai 201804, China
Jihong Guan: #x2020;Department of Computer Science and Technology, Tongji University, Shanghai 201804, China
Zhongzhi Zhang: #x2021;School of Computer Science and Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai 200433, China

International Journal of Information Technology & Decision Making (IJITDM), 2017, vol. 16, issue 05, 1359-1385

Abstract: Extracting the hierarchical organization of networks is currently a pressing task for understanding complex networked systems. The hierarchy of a network is essentially defined by the heterogeneity of link densities of communities at different scales. Here, we define a top-level partition (TLP) as a bipartition of the network (or a sub-network) such that no top-level community (TLC) runs across the two parts. It has been found that a TLP generally has a higher modularity than a non-top-level (TLP) partition when their TLCs have similar sizes and when the link densities of neighboring levels are well separated from each other. A spectral TLP procedure is proposed here to search for TLPs of a network (or sub-network). To extract the hierarchical organization of large complex networks, an algorithm called TLPA has been developed based on the TLP. Experiments have shown that the method developed in this research extract hierarchy accurately from network data.

Keywords: Hierarchical organization; complex network; spectral method; top-level partition (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S021962201450028X

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