Clustering Terrorist Groups Using Their Activity and Lethality Measures

Analyzing terrorist groups’ trends using innovative Data Analysis techniques was widely used in many research fields related to fighting terrorism. Data analysis models are used to identify crime trends, investigate unsolved attacks, predict potential threats, etc. One motivating issue that was not widely developed in the literature is the clustering of terrorist groups based on some parameters to provide actionable information. In this study, a set of armed groups identified between 1970 and 2016 in North Africa and Middle East are investigated. These groups were partitioned based on their activity and lethality parameters that can provide highly valuable results concerning their spread and fame. This study was carried out using the open source Global Terrorism Database (GTD) dataset.