Measuring Territorial Control in Civil Wars Using Hidden Markov Models: A Data Informatics-Based Approach

TL;DR

This paper introduces a data-driven method using Hidden Markov Models to measure and analyze territorial control in civil wars, addressing data limitations and capturing subnational variations.

Contribution

It proposes a novel theoretical model linking territorial control and tactical choices, and demonstrates how HMMs can estimate control levels in civil war contexts.

Findings

HMMs effectively model territorial control dynamics

Theoretical insights connect tactical choices to control levels

Discussion of challenges and mitigation strategies for HMM application

Abstract

Territorial control is a key aspect shaping the dynamics of civil war. Despite its importance, we lack data on territorial control that are fine-grained enough to account for subnational spatio-temporal variation and that cover a large set of conflicts. To resolve this issue, we propose a theoretical model of the relationship between territorial control and tactical choice in civil war and outline how Hidden Markov Models (HMMs) are suitable to capture theoretical intuitions and estimate levels of territorial control. We discuss challenges of using HMMs in this application and mitigation strategies for future work.