Understanding gender segregation through Call Data Records: An Estonian case study

Rahul Goel, Rajesh Sharma and Anto Aasa

PLOS ONE, 2021, vol. 16, issue 3, 1-21

Abstract: Understanding segregation plays a significant role in determining the development pathways of a country as it can help governmental and other concerned agencies to prepare better-targeted policies for the needed groups. However, inferring segregation through alternative data, apart from governmental surveys remains limited due to the non-availability of representative datasets. In this work, we utilize Call Data Records (CDR) provided by one of Estonia’s major telecom operators to research the complexities of social interaction and human behavior in order to explain gender segregation. We analyze the CDR with two objectives. First, we study gender segregation by exploring the social network interactions of the CDR. We find that the males are tightly linked which allows information to spread faster among males compared to females. Second, we perform the micro-analysis using various users’ characteristics such as age, language, and location. Our findings show that the prime working-age population (i.e., (24,54] years) is more segregated than others. We also find that the Estonian-speaking population (both males and females) are more likely to interact with other Estonian-speaking individuals of the same gender. Further to ensure the quality of this dataset, we compare the CDR data features with publicly available Estonian census datasets. We observe that the CDR dataset is indeed a good representative of the Estonian population, which indicates that the findings of this study reasonably reflect the reality of gender segregation in the Estonian Landscape.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0248212

DOI: 10.1371/journal.pone.0248212

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