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.
Bibliographical noteFunding Information:
Abel and DeWaard contributed equally as lead authors. Abel acknowledges the support from the National Science Foundation of China, General Program (No. 41871142). DeWaard acknowledges support from center grant #P2C HD041023 to the Minnesota Population Center at the University of Minnesota from the Eunice Kennedy Shriver National Institute of Child Health and Human Development. Ha's work was supported by a center grant provided by Nutifood and VinaCapital Foundation to the Institute for Circular Economy Development at Vietnam National University—Ho Chi Minh City. Almquist acknowledges support from Eunice Kennedy Shriver National Institute of Child Health and Human Development training grant, T32 HD101442‐01, and a research infrastructure grant, P2C HD042828, to the Center for Studies in Demography and Ecology at the University of Washington. Earlier versions of this paper were presented at the annual meetings of the British Society for Population Studies on September 14, 2016, and the Population Association of America on April 2, 2016, and April 26, 2018. The authors would like to thank the reviewers and Joint Editor for their comments and suggestions on earlier versions.
National Natural Science Foundation of China, General Program, Grant/Award Number: 41871142; Eunice Kennedy Shriver National Institute of Child Health and Human Development, Grant/Award Numbers: P2C HD041023, P2C HD041023, T32 HD101442‐01; Nutifood and VinaCapital Foundation to the Institute for Circular Economy Development at Vietnam National University Funding information
© 2021 John Wiley & Sons, Ltd.
- community detection
- directed networks
- international migration
- migration flows
- migration networks
- migration systems