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Social Network Analysis and Mining

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01-12-2021 | Original Article

Studying segregation in Estonia using call data records

Authors: Rahul Goel, Rajesh Sharma, Anto Aasa

Published in: Social Network Analysis and Mining | Issue 1/2021

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Abstract

Studying segregation between populations of different ages, ethnicities and social classes has been a prominent theme for at least half a century. To measure segregation, past works often use governmental surveys due to the scarcity of reliable data. In this work, we used call data records (CDR) provided by one of the largest mobile operators in Estonia, for studying segregation behavior based on gender, age, language and county. We consider commonly used Freeman’s segregation index for measuring segregation. Our findings suggest that (1) Gender: gender segregation exists in Estonia and its traces are visible in individuals calling hours, connectivity among age-groups, preferred language of communication, calling county and at the workplace; (2) Age: the prime working individuals (i.e., (25–54) age-group) and elderly (i.e., (64–100) age-group) are more segregated; and (3) Language: Estonian-speaking and Russian-speaking individuals are segregated based on language.

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Title: Studying segregation in Estonia using call data records
Authors: Rahul Goel
Rajesh Sharma
Anto Aasa
Publication date: 01-12-2021
Publisher: Springer Vienna
Published in: Social Network Analysis and Mining / Issue 1/2021
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-021-00817-0

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