Patterns in conflict dynamics in Yemen and Syria
- 1Department of Statistics, The George Washington University 1 , Washington, DC, USA
- 2Department of Physics, The George Washington University 2 , Washington, DC, USA
Abstract
Conflict fatalities tend to follow heavy-tailed statistical distributions. A 2005 fusion–fission theory predicts that, when armed groups operate through dynamically forming and fragmenting clusters, the number of fatalities per event should be approximated by a power-law distribution with exponent α near 2.5, with deviations reflecting the relative robustness of larger versus smaller fighter clusters. We use Armed Conflict Location and Event Data (ACLED) event-level fatality data to estimate α in recent Yemen and Syria conflict periods during 2023–2025. These conflict event datasets are small, incomplete and imperfect and only produce very crude approximations to a power law; nonetheless, the best-fit α values occupy the range 2.5<α<3.5 across most periods, which is broadly consistent with predominantly fragmented or weakly consolidated armed-group organization. Temporary reductions in α are broadly consistent with episodes in which larger coordinated clusters become more consequential. More rigorous testing will require improved datasets to become available in the future.
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BibTeX
@article{abdou2026patterns,
title = {{Patterns in conflict dynamics in Yemen and Syria}},
author = {Samar Moussa Abdou and Neil F. Johnson},
journal = {Royal Society Open Science},
year = {2026},
month = nov,
doi = {10.1098/rsos.260467},
url = {https://royalsocietypublishing.org/rsos/article/13/11/260467/483990/Patterns-in-conflict-dynamics-in-Yemen-and},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Patterns in conflict dynamics in Yemen and Syria
AU - Samar Moussa Abdou
AU - Neil F. Johnson
PY - 2026
DA - 2026/11/04
JO - Royal Society Open Science
DO - 10.1098/rsos.260467
UR - https://royalsocietypublishing.org/rsos/article/13/11/260467/483990/Patterns-in-conflict-dynamics-in-Yemen-and
AB - Conflict fatalities tend to follow heavy-tailed statistical distributions. A 2005 fusion–fission theory predicts that, when armed groups operate through dynamically forming and fragmenting clusters, the number of fatalities per event should be approximated by a power-law distribution with exponent α near 2.5, with deviations reflecting the relative robustness of larger versus smaller fighter clusters. We use Armed Conflict Location and Event Data (ACLED) event-level fatality data to estimate α in recent Yemen and Syria conflict periods during 2023–2025. These conflict event datasets are small, incomplete and imperfect and only produce very crude approximations to a power law; nonetheless, the best-fit α values occupy the range 2.5<α<3.5 across most periods, which is broadly consistent with predominantly fragmented or weakly consolidated armed-group organization. Temporary reductions in α are broadly consistent with episodes in which larger coordinated clusters become more consequential. More rigorous testing will require improved datasets to become available in the future.
SN - 2054-5703
ER -