Modeling Conflict Dynamics with Spatio-temporal Data

Modeling Conflict Dynamics with Spatio-temporal Data
Michael Dewar, Guido Sanguinetti, Visakan Kadirkamanathan, Andrew Zammit-Mangion, Anaïd Flesken
About this book
This authored monograph presents the use of dynamic spatiotemporal modeling tools for the identification of complex underlying processes in conflict, such as diffusion, relocation, heterogeneous escalation, and volatility. The authors use ideas from statistics, signal processing, and ecology, and provide a predictive framework which is able to assimilate data and give confidence estimates on the predictions. The book also demonstrates the methods on the WikiLeaks Afghan War Diary, the results showing that this approach allows deeper insights into conflict dynamics and allows a strikingly statistically accurate forward prediction of armed opposition group activity in 2010, based solely on data from preceding years. The target audience primarily comprises researchers and practitioners in the involved fields but the book may also be beneficial for graduate students.
Details
- OL Work ID
- OL20875210W
Subjects
WarViolenceData miningPhysicsDistribution (Probability theory)EngineeringSocio- and Econophysics, Population and Evolutionary ModelsMathematics in the Humanities and Social SciencesComplexityProbability Theory and Stochastic ProcessesImage and Speech Processing Signal