Skip to main content
placeholder image

Point process modelling of the Afghan War Diary

Journal Article


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.

Authors


  •   Zammit-Mangion, Andrew
  •   Dewar, Michael (external author)
  •   Kadirkamanathan, V (external author)
  •   Sanguinetti, Guido (external author)

Publication Date


  • 2012

Citation


  • Mangion, A. Zammit., Dewar, M., Kadirkamanathan, V. & Sanguinetti, G. (2012). Point process modelling of the Afghan War Diary. Proceedings of the National Academy of Sciences (PNAS), 109 (31), 12414-12419.

Scopus Eid


  • 2-s2.0-84864521921

Has Global Citation Frequency


Number Of Pages


  • 5

Start Page


  • 12414

End Page


  • 12419

Volume


  • 109

Issue


  • 31

Place Of Publication


  • United States

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.

Authors


  •   Zammit-Mangion, Andrew
  •   Dewar, Michael (external author)
  •   Kadirkamanathan, V (external author)
  •   Sanguinetti, Guido (external author)

Publication Date


  • 2012

Citation


  • Mangion, A. Zammit., Dewar, M., Kadirkamanathan, V. & Sanguinetti, G. (2012). Point process modelling of the Afghan War Diary. Proceedings of the National Academy of Sciences (PNAS), 109 (31), 12414-12419.

Scopus Eid


  • 2-s2.0-84864521921

Has Global Citation Frequency


Number Of Pages


  • 5

Start Page


  • 12414

End Page


  • 12419

Volume


  • 109

Issue


  • 31

Place Of Publication


  • United States