Modeling human conflict and terrorism across geographic scales

Abstract

We discuss the nature and origin of patterns emerging in the timing and severity of violent events within human conflicts and global terrorism. The underlying data are drawn from across geographical scales from municipalities up to entire continents, with great diversity in terms of terrain, underlying cause, socioeconomic and political setting, cultural and technological background. The data sources are equally diverse, being drawn from all available sources including non-government organizations, academia, and official government records. Despite these implicit heterogeneities and the seemingly chaotic nature of human violence, the patterns that we report are remarkably robust. We argue that this ubiquity of a particular pattern reflects a common way in which groups of humans fight each other, particularly in the asymmetric setting in which one weaker but ostensibly more adaptable opponent confronts a stronger but potentially more sluggish opponent. We propose a minimal generative model which reproduces these common statistical patterns while offering a physical explanation as to their cause. We also explain why our mechanistic approach, which is inspired by non-equilibrium statistical physics, fits naturally within the framework of recent ideas within the social science literature concerning analytical sociology, as well as setting our results in the wider context of real-world and cyber-based collective violence and illicit activity.