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Human migration patterns influence the redistribution of populationcharacteristics over the geography and since such distributions are closelyrelated to social and economic outcomes, investigating the structure anddynamics of internal migration plays a crucial role in understanding anddesigning policies for such systems. We provide an in-depth investigation intothe structure and dynamics of the internal migration in Turkey from 2008 to2020. We identify a set of classical migration laws and examine them viavarious methods for signed network analysis, ego network analysis,representation learning, temporal stability analysis, community detection, andnetwork visualization. The findings show that, in line with the classicalmigration laws, most migration links are geographically bounded with severalexceptions involving cities with large economic activity, major migration flowsare countered with migration flows in the opposite direction, there arewell-defined migration routes, and the migration system is generally stableover the investigated period. Apart from these general results, we also provideunique and specific insights into Turkey. Overall, the novel toolset we employfor the first time in the literature allows the investigation of selectedmigration laws from a complex networks perspective and sheds light on futuremigration research on different geographies.

Investigating internal migration with network analysis and latent space representations: An application to Turkey