Comparing Classification Trees to Discern Patterns of Terrorism

Objective Though applied widely in the fields of medicine, finance, ecology, psychology, and computer science, machine learning algorithmic‐based methods are a relatively novel approach to social scientific analysis that have yet to be extensively applied. Yet as we argue in this article, a specific form of algorithmic analysis known as C4.5 classification trees has much to offer social analysis and, specifically, the study of social and political violence. Method This article describes four novel classification model comparison techniques for the C4.5 classification method and applies them to the study of terrorism. Results Our state‐level analysis suggests that there is something fundamentally different in the targeting choices of religious and secular terrorists. Conclusion This analysis highlights the ability of classification trees to heighten our understanding of terrorism and even provide recommendations to policymakers for avoiding future attacks.