Comparing classification trees to discern patterns of terrorism*

Abstract

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 fournovelclassificationmodelcomparisontechniquesfortheC4.5classificationmethodandapplies 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.