AI-Driven Research on International Relations: A Case Study of Southeast Asian Countries

Abstract

The use of artificial intelligence (AI) technologies to predict conflict and cooperation has emerged as a new direction in the field of international relations research. This paper aims to utilize AI technologies—including text mining, machine learning, complex network analysis, and social network analysis—to transform states, international organizations, and other actors, along with their interactions (diplomacy, trade, conflict, and cooperation), into dynamic networks that are computable, simulable, and predictable. Taking China and Southeast Asian nations as a case study, this paper employs this dynamic network to analyze China’s bilateral relations with the eleven Southeast Asian countries and explore the evolving characteristics of international relations. The results indicate that the evolution of geopolitical relations between China and Southeast Asian countries generally follows a phased, gradual progression. International conflicts have undergone three distinct evolutionary stages (1979–1990, 1991–2011, 2012–2025). In the first stage, conflicts were notably concentrated in Vietnam, with relatively high levels of conflict also observed in Thailand, Cambodia, and China; in the second stage, the proportion of conflict scores involving Vietnam, Cambodia, and Laos declined significantly, while Thailand’s remained largely unchanged and the proportions for other countries increased; in the third stage, the trends in cooperation and conflict among countries across all stages were broadly similar, though conflict fluctuated more dramatically than cooperation, and China’s levels of cooperation and conflict increased as Southeast Asian countries’ economic dependence on China deepened.