TY - JOUR
T1 - Scaling theory of armed-conflict avalanches
AU - Lee, Edward D.
AU - Daniels, Bryan C.
AU - Myers, Christopher R.
AU - Krakauer, David C.
AU - Flack, Jessica C.
N1 - Funding Information:
We thank Guru Khalsa, Jaron Kent-Dobias, Van Savage, and Sid Redner for insightful discussion. E.D.L. acknowledges funding from the Omega Miller Program, SFI Science, and Cornell University Graduate School. We acknowledge NSF 0904863 (J.C.F. and D.C.K.), St. Andrews Foundation Grant No. 13337 (E.D.L., J.C.F. and D.C.K.), John Templeton Foundation Grant No. 60501 (J.C.F. and D.C.K.), the Proteus Foundation (J.C.F.), and the Bengier Foundation (J.C.F.). E.D.L., B.C.D., J.C.F., and D.C.K. contributed to ideation; E.D.L., B.C.D., and C.R.M. constructed the model and performed the analysis; E.D.L. and B.C.D. drafted the manuscript, and all authors contributed to editing.
Publisher Copyright:
© 2020 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.
PY - 2020/10/28
Y1 - 2020/10/28
N2 - Armed conflict data display features consistent with scaling and universal dynamics in both social and physical properties like fatalities and geographic extent. We propose a randomly branching armed conflict model to relate the multiple properties to one another. The model incorporates a fractal lattice on which conflict spreads, uniform dynamics driving conflict growth, and regional virulence that modulates local conflict intensity. The quantitative constraints on scaling and universal dynamics we use to develop our minimal model serve more generally as a set of constraints for other models for armed conflict dynamics. We show how this approach akin to thermodynamics imparts mechanistic intuition and unifies multiple conflict properties, giving insight into causation, prediction, and intervention timing.
AB - Armed conflict data display features consistent with scaling and universal dynamics in both social and physical properties like fatalities and geographic extent. We propose a randomly branching armed conflict model to relate the multiple properties to one another. The model incorporates a fractal lattice on which conflict spreads, uniform dynamics driving conflict growth, and regional virulence that modulates local conflict intensity. The quantitative constraints on scaling and universal dynamics we use to develop our minimal model serve more generally as a set of constraints for other models for armed conflict dynamics. We show how this approach akin to thermodynamics imparts mechanistic intuition and unifies multiple conflict properties, giving insight into causation, prediction, and intervention timing.
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U2 - 10.1103/PhysRevE.102.042312
DO - 10.1103/PhysRevE.102.042312
M3 - Article
C2 - 33212735
AN - SCOPUS:85094830107
VL - 102
JO - Physical Review E - Statistical, Nonlinear, and Soft Matter Physics
JF - Physical Review E - Statistical, Nonlinear, and Soft Matter Physics
SN - 1539-3755
IS - 4
M1 - 042312
ER -