Point process modelling of the Afghan War Diary

Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Guido Sanguinetti

Research output: Contribution to journalArticle (Academic Journal)

69 Citations (Scopus)

Abstract

Modern conflicts are characterized by an ever increasing use of information and sensing technology, resulting in vast amounts of high resolution data. Modelling and prediction of conflict, however, remain challenging tasks due to the heterogeneous and dynamic nature of the data typically available. Here we propose the use of dynamic spatiotemporal modelling tools for the identification of complex underlying processes in conflict, such as diffusion, relocation, heterogeneous escalation, and volatility. Using ideas from statistics, signal processing, and ecology, we provide a predictive framework able to assimilate data and give confidence estimates on the predictions. We demonstrate our methods on the WikiLeaks Afghan War Diary. Our results show that the 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 previous years.
Original languageEnglish
Pages (from-to)12414-9
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume109
Issue number31
DOIs
Publication statusPublished - 31 Jul 2012

Keywords

  • Afghan Campaign 2001-
  • Ecology
  • History, 21st Century
  • Humans
  • Models, Theoretical

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