恐怖主义
分类
数据库
政治学
计算机科学
计算机安全
数据科学
人工智能
法学
作者
Zonghuang Xu,Lin Yao,Hongyu Cai,Wei Zhang,Shi Jin,Lingyun Situ
标识
DOI:10.1057/s41599-024-03597-y
摘要
Risk assessment and categorization of terrorist attacks can assist enhance awareness of terrorism and give crucial information support for anti-terrorism efforts. This study utilizes quantitative approaches for the risk assessment and categorization of terrorist attacks. A total of 210,454 terrorist attacks that occurred worldwide from 1970 through 2020 were collected in the Global Terrorism Database, and 22 indicators related to the risk of terrorist attacks were selected. Then, the moment estimation theory and four comprehensive evaluation models were utilized to identify the top 10 riskiest terrorist attacks in the world. Furthermore, the five clustering analysis methods and three evaluation criteria were performed for the risk categorization of terrorist attacks, and the visual analysis was carried out using the kernel density estimation method. The research results have identified the top 10 riskiest global terrorist attacks, which were led by the September 11 terrorist attack event, along with their downward counterfactual events. The spatial distribution of global terrorist attack risk is primarily composed of four “turbulent cores” in the region of Central Asia, Middle East & North Africa, South Asia, and Central America & Caribbean. This study also provided insights and recommendations for anti-terrorism efforts. It has realized the risk assessment and categorization of terrorist attacks, aiding in the swift identification of its risk levels, and holds immense significance for safeguarding global national security and societal stability under new circumstances.
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