Abstract
Armed conflict data display features consistent with scaling and universal dynamics in both social and physical properties like fatalities and geographic extent. We propose a randomly branching armed conflict model to relate the multiple properties to one another. The model incorporates a fractal lattice on which conflict spreads, uniform dynamics driving conflict growth, and regional virulence that modulates local conflict intensity. The quantitative constraints on scaling and universal dynamics we use to develop our minimal model serve more generally as a set of constraints for other models for armed conflict dynamics. We show how this approach akin to thermodynamics imparts mechanistic intuition and unifies multiple conflict properties, giving insight into causation, prediction, and intervention timing.
Highlights
As Napoléon Bonaparte once said, “The battlefield is a scene of constant chaos.” The role of chance in armed conflict is cited in the classic texts on warfare, Sun-Tzu’s The Art of War, Lanchester’s Aircraft in Warfare, and Von Clausewitz’s Vom Kriege
It is difficult to refute the argument that geography plays a defining role in this conflict avalanche’s spread
In the face of many such particulars, the statistics that emerge from the ensemble display highly regular, emergent properties aligned with self-consistent power-law scaling and universal dynamics
Summary
As Napoléon Bonaparte once said, “The battlefield is a scene of constant chaos.” The role of chance in armed conflict is cited in the classic texts on warfare, Sun-Tzu’s The Art of War, Lanchester’s Aircraft in Warfare, and Von Clausewitz’s Vom Kriege. By studying the Armed Conflict Location & Event Data (ACLED) Project [7], multiple quantitative regularities that we unify in a simple scaling framework [8]. Such regularities are evocative of scaling laws that emerge in disordered, driven physical systems [9], in animal societies with long temporal correlations in conflict dynamics [10], elections [11], and cities [12], among other social systems [13]. On this geography, and scale-free fluctuations in virulence, or intensity, between conflicts We extract these regularities from the statistics of conflict avalanches, consisting of spatiotemporally proximate events that have been joined into clusters.
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