Presently, there is no agreed upon data‐driven approach for identifying the geographic boundaries of migration networks that international migration systems are ultimately manifested in. Drawing from research on community detection methods, we introduce and apply the Information Theoretic Community Detection Algorithm for identifying and studying the geographic boundaries of migration networks. Using a new set of estimates of country‐to‐country migration flows every 5 years from 1990 to 1995 to 2010–2015, we trace the form and evolution of international migration networks over the past 25 years. Consistent with the concept of dynamic stability, we show that the number, size and internal country compositions of international migration networks have been remarkably stable over time; however, we also document many short‐term fluctuations. We conclude by reflecting on the spirit of our work in this paper, which is to promote consensus around tools and best practices for identifying and studying international migration networks.