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Conflict and Cooperation in an Actors' Network of Chechnya Based on Event Data

Author

Listed:
  • August Hämmerli

    (FAST, swisspeace, Bern; Swiss Federal Institute of Technology, Zurich)

  • Regula Gattiker
  • Reto Weyermann

    (Early Warning Unit, FAST, swisspeace, Bern)

Abstract

The conflict in Chechnya is characterized by a high degree of complexity. To capture this complexity, the authors produced an actors' network analysis drawing on one of the largest event databases today. The aim was to identify the main actors involved in the conflict, track down the most important conflictive and cooperative ties between actors, and compare the quality and intensity of interactions among actor groups. In total, 2,818 events reported between 2002 and 2005 were assigned forty-four actors categories. Measures of centrality and power and a combination of principal component and cluster analysis were used to produce graphs of the network. The authors found civilians to be the most important actors, closely followed by the Russian military, the Chechen fighters, and the Chechen government. The results are discussed in light of the current situation in Chechnya with reference to chances and limitations of the network approach with event data.

Suggested Citation

  • August Hämmerli & Regula Gattiker & Reto Weyermann, 2006. "Conflict and Cooperation in an Actors' Network of Chechnya Based on Event Data," Journal of Conflict Resolution, Peace Science Society (International), vol. 50(2), pages 159-175, April.
    • Handle: RePEc:sae:jocore:v:50:y:2006:i:2:p:159-175
    DOI: 10.1177/0022002705284826
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    References listed on IDEAS

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    3. Hoff, Peter D. & Ward, Michael D., 2004. "Modeling Dependencies in International Relations Networks," Political Analysis, Cambridge University Press, vol. 12(2), pages 160-175, April.
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    Cited by:

    1. Wang, Qingyun & Cao, Shengyu & Xiao, Yayuan, 2019. "Statistical characteristics of international conflict and cooperation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).

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