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  4. Segregation and Sentiment: Estimating Refugee Segregation and Its Effects Using Digital Trace Data
 
book part or chapter

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

Marquez, Neal
•
Garimella, Kiran  
•
Toomet, Ott
Show more
January 1, 2019
Guide to Mobile Data Analytics in Refugee Scenarios: The ‘Data for Refugees Challenge’ Study

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. Most of the existing literature on the integration and assimilation of Syrian refugees in Turkey has taken the form of surveys assessing the degree to which Syrian refugees feel they are part of Turkish culture and the way Turkish natives view the refugee population. Our analysis leverages call detail record data, made available by the Data for Refugees (D4R) Challenge, to assess how communication and segregation vary between Turkish natives and Syrian refugees over time and space. In addition, we test how communication and segregation vary with measures of hostility from Turkish natives using data from the social media platform Twitter. We find that measures of segregation vary significantly over time and space. We also find that measures of intergroup communication positively correlate with measures of public sentiment toward refugees. Attempts to address the concerns of Turkish natives in order to minimize the traction of online hate movements may help to improve the integration process.

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Type
book part or chapter
DOI
10.1007/978-3-030-12554-7_14
Scopus ID

2-s2.0-105009146358

Author(s)
Marquez, Neal

University of Washington

Garimella, Kiran  

École Polytechnique Fédérale de Lausanne

Toomet, Ott

University of Washington

Weber, Ingmar G.

Qatar Computing Research Institute

Zagheni, Emilio

University of Washington

Date Issued

2019-01-01

Publisher

Springer International Publishing

Published in
Guide to Mobile Data Analytics in Refugee Scenarios: The ‘Data for Refugees Challenge’ Study
DOI of the book
10.1007/978-3-030-12554-7
ISBN of the book

9783030125547

9783030125530

Start page

265

End page

282

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
EPFL  
Available on Infoscience
August 20, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/253277
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