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Research on the Dynamic Change of Terrorist Organization Cooperation from the Big Data Perspective

机译:大数据视角与恐怖组织合作动态变化研究

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Understanding the interactive relations of terrorist organizations is quite helpful for the security department in counter-terrorism. Emerging researches have studied the consequence and influential factors of these relations based on cross-sectional data. However, the dynamic changing of relations between different terrorist organizations over time has not yet been addressed adequately. Longitudinal Network Analysis is considered as an effective method in the studies of political violence, especially based on the Big Data from open source intelligence. In this paper, a framework is proposed for the quantitative analysis of the dynamic change of cooperation relations based on the longitudinal network model. The results have shown that more and more cooperation can be seen between terrorist organizations over time. Although the networks are loosely connected, the rapid expansion of the network scale will have a threat on the international society and lead to the explosion of global terrorist attacks. Important organizations actively involved in cooperation in recent years have also been identified.
机译:了解恐怖主义组织的互动关系对反恐怖主义的安全部门非常有帮助。基于横截面数据,新兴研究已经研究了这些关系的后果和影响因素。但是,随着时间的推移,不同恐怖组织之间的关系的动态改变尚未得到充分解决。纵向网络分析被视为政治暴力研究中的有效方法,特别是根据开源智能的大数据。本文提出了一种框架,用于基于纵向网络模型的合作关系动态变化的定量分析。结果表明,随着时间的推移,恐怖组织之间可以看到越来越多的合作。虽然网络是松散连接的,但网络规模的快速扩张将对国际社会产生威胁,并导致全球恐怖袭击的爆发。还确定了近年来积极参与合作的重要组织。

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