Title: Winning the war on terror: using social networking tools and GTD to analyse the regularity of terrorism activities

Authors: Xuan Guo; Fei Xu; Zhiting Xiao; Hongguo Yuan; Xiaoyuan Yang

Addresses: Officers' College of PAP, Chengdu, China; College of Information and Communication, National University of Defense Technology, Wuhan, China ' College of Information and Communication, National University of Defense Technology, Wuhan, China ' College of Information and Communication, National University of Defense Technology, Wuhan, China ' Officers' College of PAP, Chengdu, China ' Engineering University of PAP, Xi'an, China

Abstract: In order to study the spatiotemporal characteristics and activity patterns of terrorism attacks in China, so as to make effective counter-terrorism strategies, two kinds of different intelligence sources were analysed by means of social network analysis and mathematical statistics. Firstly, using the social network analysis tool ORA, we build a terrorists' activity meta-network for the text information, extracting the four categories of person, places, organisations and time, and analyse the characteristics of the key nodes of the network, then the meta-network is decomposed into person-organisation and person-location, organisation-location, organisation-time four binary subnets to analyse the temporal and spatial characteristics of terrorist activities. Then, using GTD data set to analyse the characteristics of China's terrorist attacks from 1989 to 2015, the geo-spatial distribution and time distribution of terrorist events are summarised. Combined with the data visualisation method, the previous results of social network analysis using open source text are verified and compared; finally we put forward some suggestions on counter-terrorism prevention strategy in China.

Keywords: SNA; social network analysis; GTD; meta-network; ORA; counter-terrorism; terrorism activities.

DOI: 10.1504/IJGUC.2019.100879

International Journal of Grid and Utility Computing, 2019 Vol.10 No.4, pp.422 - 437

Received: 29 Jan 2018
Accepted: 06 Mar 2018
Published online: 19 Jul 2019 *

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