Statistical characteristics of international conflict and cooperation network

Abstract

Conflict and cooperation event data can be used to build complex networks to study international relations systematically. In this paper, using complex network methods, we studied the statistical characteristics of a series of international conflict and cooperation networks built using machine coding event data. The result shows that in those networks, the cumulative distributions of degrees, edge weights, and vertex strengths follow the shifted power law. By analyzing the disparity in weights, average nearest neighbor degrees, clustering coefficients, and rich-club coefficients of those networks, we studied the corresponding features of international relations, and discussed the possible behavior pattern of states in international conflict and cooperation.