On Classifying Terrorism: A Potential Contribution of Cluster Analysis for Academics and Policymakers

Abstract

The authors argue that classifying terrorist groups based on their motivations (i.e. Islamic, nationalist-separatist, left-wing, etc) causes analysts to ignore important similarities between such groups. This article suggests using cluster analysis to classify terrorist groups based on their motives and their tactics. Using the U.S. State Department's list of Significant Terrorist Incidents through 2003, the authors demonstrate that trends in terrorist attacks among groups with seemingly disparate motives and locations provide insights into dynamic nature of terrorism over the past several decades. Specifically, certain terrorist incidents in places as diverse as Lebanon, Georgia, and Colombia have more in common than is typically suspected, suggesting that such groups monitor and learn from one another's activities.