Exploring night and day socio-spatial segregation based on mobile phone data: The case of Medellin (Colombia)

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Moya Gómez, Borja and Stępniak, Marcin and García Palomares, Juan Carlos and Frías Martínez, Enrique and Gutiérrez Puebla, Javier (2021) Exploring night and day socio-spatial segregation based on mobile phone data: The case of Medellin (Colombia). Computers, Environment and Urban Systems, 89 . p. 101675. ISSN 0198-9715

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Official URL: https://doi.org/10.1016/j.compenvurbsys.2021.101675



Abstract

Social segregation research has a long tradition in urban studies. Usually, these studies focus on the residential dimension, using official registries (e.g., census data), which show population distribution at night. Nevertheless, these studies disregard the fact that the population in cities is highly mobile, and its spatial distribution dramatically changes between night and day. The emergence of new data sources (Big Data) creates perfect conditions to consider segregation as a process, by providing the opportunity to dynamically analyse temporal changes in social segregation.
This study uses mobile phone data to analyse changes in social segregation between night and day. Our case study is Medellin (Colombia), a highly socially-segregated, South American city, where social integration policies are being developed, targeting the population in the most disadvantaged neighbourhoods. We use several complementary indicators of social segregation, supplementing them with mobility indicators that help explain changes in spatial segregation between night and day.
The main conclusion is that daily mobility reduces the concentration of a particular group within neighbourhoods and increases the degree of social mixing (exposure) in local settings. This greater social exposure softens local contrasts (outliers) and increases the extension of spatial clusters (positive spatial autocorrelation), so general clustering trends emerge more clearly. The study also makes clear that increased exposure during the day mainly occurs due to the mobility of the low-income population, who are the most likely to leave their neighbourhood during the day and who travel the greatest distances to the most diverse set of destinations.


Item Type:Article
Additional Information:

CRUE-CSIC (Acuerdos Transformativos 2021)

Uncontrolled Keywords:Social segregation, Mobile phone data, Spatial statistics, Medellin (Colombia)
Subjects:Social sciences > Sociology > Urban sociology
Humanities > Geography > Human geography
ID Code:69468
Deposited On:10 Jan 2022 12:31
Last Modified:18 Feb 2022 09:44

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