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dc.contributor.authorDong, Xiaowen
dc.contributor.authorMorales, Alfredo J
dc.contributor.authorJahani, Eaman
dc.contributor.authorMoro, Esteban
dc.contributor.authorLepri, Bruno
dc.contributor.authorBozkaya, Burcin
dc.contributor.authorSarraute, Carlos
dc.contributor.authorBar-Yam, Yaneer
dc.contributor.authorPentland, Alex
dc.date.accessioned2021-09-20T17:30:02Z
dc.date.available2021-09-20T17:30:02Z
dc.date.issued2020-07-10
dc.identifier.urihttps://hdl.handle.net/1721.1/131734
dc.description.abstractAbstract 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.en_US
dc.publisherSpringer Berlin Heidelbergen_US
dc.relation.isversionofhttps://doi.org/10.1140/epjds/s13688-020-00238-7en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceSpringer Berlin Heidelbergen_US
dc.titleSegregated interactions in urban and online spaceen_US
dc.typeArticleen_US
dc.identifier.citationEPJ Data Science. 2020 Jul 10;9(1):20en_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratory
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2020-07-11T04:04:14Z
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dspace.embargo.termsN
dspace.date.submission2020-07-11T04:04:10Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Needed


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