Segregation and Sentiment: Estimating Refugee Segregation and Its Effects Using Digital Trace Data

Neal Marquez , University of Washington, Seattle
Kiran Garimella, Qatar Computing Research Institute
Ott Toomet, University of Tartu
Ingmar Weber, Qatar Computing Research Institute
Emilio Zagheni, Max Planck Institute for Demographic Research

In light of the ongoing events of the Syrian Civil War, many governments have shifted the focus of their hospitality efforts from providing temporary shelter to sustaining this new long-term population. In Turkey, a heightened focus has been placed on the encouragement of integration of Syrian refugees into Turkish culture, through the dismantling of Syrian refugee-only schools in Turkey and attempts to grant refugees permanent citizenship, among other strategies. Our analysis leverages call detail record data, made available by the Data 4 Refugees Challenge, to assess how communication and segregation vary between Turkish natives and Syrian refugees over time and space. Additionally, we test how communication and segregation vary with measures of hostility from Turkish natives using posts about refugees from Twitter. We find measures of segregation vary significantly over time and space. We also find that measures of inter-group communication positively correlate with measures of public sentiment towards refugees.

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 Presented in Session 128. Using Social Media in Population Research