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

Int. J. Grid Util. Comput. Pub Date : 2019-06-25 DOI:10.1504/IJGUC.2019.10022137

Xuan Guo, Fei Xu, Zhiting Xiao, Hongguo Yuan, Xiao-ling Yang

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引用次数: 3

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.

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赢得反恐战争:利用社交网络工具和GTD分析恐怖活动的规律性

为了研究中国恐怖袭击的时空特征和活动模式，从而制定有效的反恐战略，采用社会网络分析和数理统计的方法对两种不同的情报来源进行了分析。首先，利用社会网络分析工具ORA对文本信息构建恐怖分子活动元网络，提取人物、地点、组织和时间四类，分析网络关键节点的特征，然后将元网络分解为人-组织和人-地点、组织-地点、组织-时间四个二元子网，分析恐怖活动的时空特征。然后，利用GTD数据集分析了1989 - 2015年中国恐怖袭击事件的特征，总结了恐怖事件的地理空间分布和时间分布。结合数据可视化方法，对以往使用开源文本进行社交网络分析的结果进行验证和比较;最后提出了中国反恐防范战略的建议。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Int. J. Grid Util. Comput.

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