Mapping the long-term trajectories of political violence in Africa

2026-03-06

AI Summary

This study addresses a critical gap in political violence research by moving beyond discrete onset and termination points to examine its spatiotemporal accumulation and evolution. Leveraging event-level ACLED data from Africa spanning 1997 to 2024, the paper pioneers an integrated approach combining longitudinal sequence analysis with spatially explicit modeling. Through optimal matching, clustering, and spatial statistics, it classifies and traces trajectories of violence intensity and spatial concentration. The analysis identifies six archetypal pathways of violent evolution—ranging from short-lived local outbreaks to protracted high-intensity conflicts—and reveals pronounced spatial dependence and cross-border linkages, particularly in border regions. By transcending conventional static frameworks, this work systematically characterizes the life cycle of political violence, offering a dynamic and nuanced understanding of its temporal dynamics and spatial interdependencies.

Technology Category

• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Social Networks and Social Media: Social media analysis through the lenses of networks
• Security and Privacy: Large-scale security measurements

Abstract

Existing models of political violence often emphasize discrete transitions, when conflicts emerge, escalate, or subside, without considering the longer trajectories of violence that accumulate across time and space. This paper introduces a spatially explicit longitudinal sequence analysis to address this gap. Using event-level data from the Armed Conflict Location and Event Dataset covering Africa from 1997 to 2024, we classify locations according to the intensity and spatial concentration of violence, tracing how these states evolve into distinct conflict trajectories. Applying optimal matching and clustering techniques, we identify six recurrent patterns ranging from short-lived, localized outbreaks to protracted high-intensity conflicts. We further assess how these trajectories align across neighboring areas, revealing evidence of spatial interdependence, particularly in border regions. By highlighting the temporal rhythms and geographic linkages of political violence, the study advances conflict research beyond isolated transitions and provides a framework for understanding the life cycles of violence.

Problem

• political violence
• long-term trajectories
• spatial interdependence
• conflict dynamics
• temporal rhythms

Innovation

• spatially explicit longitudinal sequence analysis
• optimal matching
• conflict trajectories
• spatial interdependence
• event-level data