Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/100692
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorXu, Yen_US
dc.creatorBelyi, Aen_US
dc.creatorSanti, Pen_US
dc.creatorRatti, Cen_US
dc.date.accessioned2023-08-11T03:12:43Z-
dc.date.available2023-08-11T03:12:43Z-
dc.identifier.issn1742-5689en_US
dc.identifier.urihttp://hdl.handle.net/10397/100692-
dc.language.isoenen_US
dc.publisherRoyal Society Publishingen_US
dc.rights© 2019 The Author(s) Published by the Royal Society. All rights reserved.en_US
dc.rightsThis is the peer reviewed version of the following article: Xu, Y., Belyi, A., Santi, P., & Ratti, C. (2019). Quantifying segregation in an integrated urban physical-social space. Journal of the Royal Society Interface, 16(160), 20190536, which has been published in final form at https://doi.org/10.1098/rsif.2019.0536.en_US
dc.subjectBig data analyticsen_US
dc.subjectHomophilyen_US
dc.subjectMobile phone dataen_US
dc.subjectSocial networken_US
dc.subjectSocial segregationen_US
dc.subjectUrban mobilityen_US
dc.titleQuantifying segregation in an integrated urban physical-social spaceen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume16en_US
dc.identifier.issue160en_US
dc.identifier.doi10.1098/rsif.2019.0536en_US
dcterms.abstractOur knowledge of how cities bring together different social classes is still limited. Much effort has been devoted to investigating residential segregation, mostly over well-defined social groups (e.g. race). Little is known of how mobility and human communications affect urban social integration. The dynamics of spatial and social-network segregation and individual variations along these two dimensions are largely untapped. In this article, we put forward a computational framework based on coupling large-scale information on human mobility, social-network connections and people’s socio-economic status (SES), to provide a breakthrough in our understanding of the dynamics of spatio-temporal and social-network segregation in cities. Building on top of a social similarity measure, the framework can be used to depict segregation dynamics down to the individual level, and also provide aggregate measurements at the scale of places and cities, and their evolution over time. By applying the methodology in Singapore using large-scale mobile phone and socio-economic datasets, we find a relatively higher level of segregation among relatively wealthier classes, a finding that holds for both social and physical space. We also highlight the interplay between the effect of distance decay and homophily as forces that determine communication intensity, defining a notion of characteristic ‘homophily distance’ that can be used to measure social segregation across cities. The time-resolved analysis reveals the changing landscape of urban segregation and the time-varying roles of places. Segregations in physical and social space are weakly correlated at the individual level but highly correlated when grouped across at least hundreds of individuals. The methodology and analysis presented in this paper enable a deeper understanding of the dynamics of human segregation in social and physical space, which can assist social scientists, planners and city authorities in the design of more integrated cities.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of the Royal Society interface, Nov. 2019, v. 16, no. 160, 20190536en_US
dcterms.isPartOfJournal of the Royal Society interfaceen_US
dcterms.issued2019-11-
dc.identifier.scopus2-s2.0-85075291442-
dc.identifier.pmid31744420-
dc.identifier.eissn1742-5662en_US
dc.identifier.artn20190536en_US
dc.description.validate202305 bckw-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberLSGI-0157-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHong Kong Polytechnic University Start-Up Grant; National Research Foundation, Prime Minister’s Office, Singapore; Singapore-MIT Alliance for Research and Technology (SMART) Future Urban Mobility (FM) IRGen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS24928375-
dc.description.oaCategoryGreen (AAM)en_US
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