Echoes of conflict: quantifying redundancy in fatality time series

Do wars follow predictable patterns, or are they chaotic and inherently unpredictable? We explore this question by quantifying temporal redundancy—how often similar patterns recur—in conflict-related fatalities. Using entropy-based analysis—a measure of randomness—and Dynamic Time Warping, we compare conflict dynamics with other complex systems such as seismology and finance. Our findings reveal that the dynamics of fatalities within conflicts exhibit high levels of entropy: they are largely unpredictable. Conflicts generally display higher entropy than climate or earthquake data, which highlights the challenges of predictive modeling. Moreover, conflict patterns are not region- or decade-specific, which suggests a degree of universality. Our framework distinguishes stable from chaotic phases in conflict dynamics and clarifies where forecasting is feasible.