  An emerging area of research is the study of macroscale migration patterns as
a network of nodes that represent places (e.g., countries, cities, and rural
areas) and edges that encode migration ties that connect those places. In this
chapter, we first review advances in the study of migration networks and recent
work that has employed network analysis to examine such networks at different
geographical scales. In our discussion, we focus in particular on global scale
migration networks. We then propose ways to leverage network analysis in
concert with digital technologies and online geolocated data to examine the
structure and dynamics of migration networks. The implementation of such
approaches for studying migration networks faces many challenges, including
ethical ones, methodological ones, socio-technological ones (e.g., data
availability and reuse), and research reproducibility. We detail these
challenges, and we then consider possible ways of linking digital geolocated
data to administrative and survey data as a way of harnessing new technologies
to construct increasingly realistic migration networks (e.g., using multiplex
networks). We also briefly discuss new methods (e.g., multilayer network
analysis) in network analysis and adjacent fields (e.g., machine learning) that
can help advance understanding of macroscale patterns of migration.
