The Geography of Ethnic Violence

  • Alex Rutherford
  • May Lim
  • Richard Metzler
  • Dion Harmon
  • Justin Werfel
  • Shlomiya Bar-Yam
  • Alexander Gard-Murray
  • Andreas Gros
  • Yaneer Bar-YamEmail author
Part of the Understanding Complex Systems book series (UCS)


We consider the conditions of peace and violence among ethnic groups, testing a theory designed to predict the locations of violence and interventions that can promote peace. Violence arises at boundaries between regions that are not sufficiently well defined. We model cultural differentiation as a separation of groups whose members prefer similar neighbors with a characteristic group size at which violence occurs. Application of this model to the area of the former Yugoslavia and to India accurately predicts the locations of reported conflict. Characterizing the model’s success in predicting peace requires examples where peace prevails despite diversity. Switzerland is recognized as a country of peace, stability, and prosperity. This is surprising because of its linguistic and religious diversity that in other parts of the world lead to conflict and violence. Here we analyze how peaceful stability is maintained. Our analysis shows that peace does not depend on integrated coexistence, but rather on well-defined topographical and political boundaries separating linguistic and religious groups, respectively. In exactly one region, a porous mountain range does not adequately separate linguistic groups and violent conflict has led to the recent creation of the canton of Jura. Our analysis supports the hypothesis that violence between groups can be inhibited by both physical and political boundaries. A similar analysis of the area of the former Yugoslavia shows that during widespread ethnic violence existing political boundaries did not coincide with the boundaries of distinct groups, but peace prevailed in specific areas where they did coincide.


Religious Group Actual Violence Wavelet Filter Religious Diversity Political Boundary 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank Stuart Pimm, Irving Epstein, and Lawrence Susskind for helpful comments on the manuscript, Michael Widener, Urbano França, Casey Friedman, and Blake Stacey for help with a figure and formatting. This work was supported in part by AFOSR under Grant FA9550-09-1-0324 and ONR under Grant N000140910516.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Alex Rutherford
    • 1
  • May Lim
    • 1
  • Richard Metzler
    • 1
  • Dion Harmon
    • 1
  • Justin Werfel
    • 1
  • Shlomiya Bar-Yam
    • 1
  • Alexander Gard-Murray
    • 1
  • Andreas Gros
    • 1
  • Yaneer Bar-Yam
    • 1
    Email author
  1. 1.New England Complex Systems InstituteCambridgeUSA

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