Segregated interactions in urban and online space

Abstract Urban income segregation is a widespread phenomenon that challenges societies across the globe. Classical studies on segregation have largely focused on the geographic distribution of residential neighborhoods rather than on patterns of social behaviors and interactions. In this study, we a...

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Main Authors: Xiaowen Dong, Alfredo J. Morales, Eaman Jahani, Esteban Moro, Bruno Lepri, Burcin Bozkaya, Carlos Sarraute, Yaneer Bar-Yam, Alex Pentland
Format: Article
Language:English
Published: SpringerOpen 2020-07-01
Series:EPJ Data Science
Subjects:
Online Access:http://link.springer.com/article/10.1140/epjds/s13688-020-00238-7
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spelling doaj-56c1cad4644e4505905d4e48c6bbe8602020-11-25T03:33:00ZengSpringerOpenEPJ Data Science2193-11272020-07-019112210.1140/epjds/s13688-020-00238-7Segregated interactions in urban and online spaceXiaowen Dong0Alfredo J. Morales1Eaman Jahani2Esteban Moro3Bruno Lepri4Burcin Bozkaya5Carlos Sarraute6Yaneer Bar-Yam7Alex Pentland8Department of Engineering Science, University of OxfordMedia Lab, Massachusetts Institute of TechnologyInstitute for Data, Systems and Society, Massachusetts Institute of TechnologyMedia Lab, Massachusetts Institute of TechnologyMobile and Social Computing Lab, Fondazione Bruno KesslerBehavioral Analytics & Visualization Lab, Sabancı UniversityGrandata LabsNew England Complex Systems InstituteMedia Lab, Massachusetts Institute of TechnologyAbstract Urban income segregation is a widespread phenomenon that challenges societies across the globe. Classical studies on segregation have largely focused on the geographic distribution of residential neighborhoods rather than on patterns of social behaviors and interactions. In this study, we analyze segregation in economic and social interactions by observing credit card transactions and Twitter mentions among thousands of individuals in three culturally different metropolitan areas. We show that segregated interaction is amplified relative to the expected effects of geographic segregation in terms of both purchase activity and online communication. Furthermore, we find that segregation increases with difference in socio-economic status but is asymmetric for purchase activity, i.e., the amount of interaction from poorer to wealthier neighborhoods is larger than vice versa. Our results provide novel insights into the understanding of behavioral segregation in human interactions with significant socio-political and economic implications.http://link.springer.com/article/10.1140/epjds/s13688-020-00238-7Urban segregationPurchase activityOnline communicationComputational social science
collection DOAJ
language English
format Article
sources DOAJ
author Xiaowen Dong
Alfredo J. Morales
Eaman Jahani
Esteban Moro
Bruno Lepri
Burcin Bozkaya
Carlos Sarraute
Yaneer Bar-Yam
Alex Pentland
spellingShingle Xiaowen Dong
Alfredo J. Morales
Eaman Jahani
Esteban Moro
Bruno Lepri
Burcin Bozkaya
Carlos Sarraute
Yaneer Bar-Yam
Alex Pentland
Segregated interactions in urban and online space
EPJ Data Science
Urban segregation
Purchase activity
Online communication
Computational social science
author_facet Xiaowen Dong
Alfredo J. Morales
Eaman Jahani
Esteban Moro
Bruno Lepri
Burcin Bozkaya
Carlos Sarraute
Yaneer Bar-Yam
Alex Pentland
author_sort Xiaowen Dong
title Segregated interactions in urban and online space
title_short Segregated interactions in urban and online space
title_full Segregated interactions in urban and online space
title_fullStr Segregated interactions in urban and online space
title_full_unstemmed Segregated interactions in urban and online space
title_sort segregated interactions in urban and online space
publisher SpringerOpen
series EPJ Data Science
issn 2193-1127
publishDate 2020-07-01
description Abstract Urban income segregation is a widespread phenomenon that challenges societies across the globe. Classical studies on segregation have largely focused on the geographic distribution of residential neighborhoods rather than on patterns of social behaviors and interactions. In this study, we analyze segregation in economic and social interactions by observing credit card transactions and Twitter mentions among thousands of individuals in three culturally different metropolitan areas. We show that segregated interaction is amplified relative to the expected effects of geographic segregation in terms of both purchase activity and online communication. Furthermore, we find that segregation increases with difference in socio-economic status but is asymmetric for purchase activity, i.e., the amount of interaction from poorer to wealthier neighborhoods is larger than vice versa. Our results provide novel insights into the understanding of behavioral segregation in human interactions with significant socio-political and economic implications.
topic Urban segregation
Purchase activity
Online communication
Computational social science
url http://link.springer.com/article/10.1140/epjds/s13688-020-00238-7
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