Patterns in Conflict Dynamics in Yemen and Syria

TL;DR

This study analyzes conflict event data from Yemen and Syria, revealing that fatalities follow power-law distributions with exponents indicating persistent small-cluster operations and potential early-warning signals during crises.

Contribution

It applies a mathematical model to recent conflict data, providing new insights into cluster dynamics and identifying potential early-warning indicators based on exponent variations.

Findings

Fatalities follow power-law distributions with exponents between 2.5 and 3.5.

Larger clusters temporarily become more involved during crises.

Exponent reductions may serve as early-warning signals for major battles.

Abstract

Conflict fatalities tend to follow heavy-tailed statistical distributions. A 2005 fusion-fission theory predicts mathematically that for armed groups operating in dynamically evolving clusters within a given conflict, the number of fatalities per conflict event will follow an approximate power-law distribution with exponent near 2.5, with the specific exponent value offering insight into the relative robustness of larger versus smaller clusters of fighters in that armed group. Since Yemen and Syria are current hotspots for future conflict, yet their most recent conflicts (2023-2025) have not been studied at the event level, we use ACLED data to determine their best-fit exponent value as each conflict evolved. We find that the exponent lies between 2.5 and 3.5 predominantly throughout each conflict, which suggests that the fighters in each of these conflicts continued to operate in smaller clusters as the conflict evolved. Moreover, temporary reductions in the exponent value -- which suggests a temporary increase in the robustness and involvement of larger clusters of fighters -- appear to arise during major crises ahead of the largest battles. Though the lack higher-quality data for these conflicts prevents us from establishing this more firmly, such a temporary reduction in the exponent value hints at its potential use as an early-warning signature.