NDLI: Network analysis of terrorist activities

Content Provider	Springer Nature Link
Author	Fu, Julei Fan, Ying Wang, Yang Wang, Shouyang
Copyright Year	2014
Abstract	This paper uses an extensive network approach to “East Turkistan” activities by building both the one-mode and the bipartite networks for these activities. In the one-mode network, centrality analysis and spectrum analysis are used to describe the importance of each vertex. On this basis, two types of core vertices — The center of communities and the intermediary vertices among communities — are distinguished. The weighted extreme optimization (WEO) algorithm is also applied to detect communities in the one-mode network. In the “terrorist-terrorist organization” bipartite network, the authors adopt centrality analysis as well as clustering analysis based on the original bipartite network in order to calculate the importance of each vertex, and apply the edge clustering coefficient algorithm to detect the communities. The comparative and empirical analysis indicates that this research has been proved to be an effective way to identify the core members, key organizations, and communities in the network of “East Turkistan” terrorist activity. The results can provide a scientific basis for the analysis of “East Turkistan” terrorist activity, and thus provide decision support for the real work of “anti-terrorism”.
Starting Page	1079
Ending Page	1094
Page Count	16
File Format	PDF
ISSN	10096124
Journal	Journal of Systems Science and Complexity
Volume Number	27
Issue Number	6
e-ISSN	15597067
Language	English
Publisher	Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Publisher Date	2014-08-28
Publisher Place	Beijing
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Anti-terrorism complex networks terrorist activity network vertex centrality Systems Theory, Control Operations Research/Decision Theory Mathematics of Computing Statistical Physics, Dynamical Systems and Complexity Statistics
Content Type	Text
Resource Type	Article
Subject	Information Systems

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