Segregation and “Silent Separation”: Using Large-Scale Network Data to Model the Determinants of Ethnic Segregation

Joshua E. Blumenstock, University of Washington
Ott Toomet, University of Tartu

We exploit a novel source of data to model the impact of migration and urbanization on segregation in Estonia. Analyzing the complete mobile phone records of hundreds of thousands of Estonians, we observe the ethnicity of each individual on the network (Russian or Estonian), the complete history of locations visited by each individual, and hundreds of millions of phone-based interactions taking place over the network. We find that the ethnic composition of an individual’s geographic neighborhood heavily influences the structure of the individual’s phone-based network. We further find that patterns of segregation are significantly different for migrants than for the at-large population: migrants are more likely to interact with coethnics than non-migrants, but are less sensitive to the ethnic composition of their immediate neighborhood than non-migrants. Interpreted these results with a nested search-based model of friendship formation, we test between different determinants of ethnic segregation in Estonia.