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Conflict Management and Peace Science
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Dynamics of International Mediation: Analysis Using Machine Learning Methods

Anne-Katrin Wickboldt

Massachusetts Institute of Technology

Jacob Bercovitch

University of Canterbury, Christchurch, New Zealand

Selwyn Piramuthu

University of Pennsylvania

This paper develops a framework to help us understand the dynamics of international mediation efforts and their consequences. This approach identifies the relevant variables that influence the success of these mediation efforts as well as the relationships among these variables in influencing mediation outcomes. The framework incorporates techniques that have been developed under the rubric of machine learning, specifically feature selection and induced decision trees. In addition to confirming some results from previous studies, results from this study provide new insights on some of the most important factors affecting international mediation.

Conflict Management and Peace Science, Vol. 17, No. 1, 49-68 (1999)
DOI: 10.1177/073889429901700102
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