Measuring Territorial Control in Civil Wars Using Hidden Markov Models: A Data Informatics-Based Approach
Applications
2018-01-23 v2 Computers and Society
Physics and Society
Machine Learning
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.
Keywords
Cite
@article{arxiv.1711.06786,
title = {Measuring Territorial Control in Civil Wars Using Hidden Markov Models: A Data Informatics-Based Approach},
author = {Therese Anders and Hong Xu and Cheng Cheng and T. K. Satish Kumar},
journal= {arXiv preprint arXiv:1711.06786},
year = {2018}
}
Comments
Presented at NIPS 2017 Workshop on Machine Learning for the Developing World