Quantitative Research on Global Terrorist Attacks and Terrorist Attack Classification

• Main Authors: Xueli Hu, Fujun Lai, Gufan Chen, Rongcheng Zou, Qingxiang Feng
• Format: Article
• Language: English
• Published: MDPI AG 2019-03-01
• Series: Sustainability
• Subjects: terrorist attacks; factor analysis; K-means clustering
• Online Access: http://www.mdpi.com/2071-1050/11/5/1487

Terrorist attacks are events which hinder the development of a region. Before the terrorist attacks, we need to conduct a graded evaluation of the terrorist attacks. After getting the level of terrorist attacks, we can fight terrorist organizations more effectively. This paper builds rating models for terrorist attacks, hidden or emerging terrorist organization classification discovery models, terrorist organization alliance network models and more, through quantitative research of the Global Terrorism Database, which solved the event classification. Through studying relevant literature and the variables of the Global Terrorism Database, this paper sorted out 25 observation variables related to the impact level (level of harm) of terrorist attacks. By establishing a mathematical model of factor analysis, 11 factors related to the impact level (level of harm) of terrorist attacks were constructed, and the variance of the contribution of each factor was used as the weight to calculate the comprehensive rate of the impact level of each terrorist attack. Finally, K-means clustering method is used to cluster and analyze the comprehensive rate of impact level, and the top 10 terrorist attacks with the highest impact level in the past two decades were obtained.