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Заглавие документа: Quantifying segregation in an integrated urban physical-social space
Авторы: Xu, Y.
Belyi, A.
Santi, P.
Ratti, C.
Тема: ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика
ЭБ БГУ::ОБЩЕСТВЕННЫЕ НАУКИ::Социология
Дата публикации: 2019
Издатель: Royal Society Publishing
Библиографическое описание источника: J R Soc Interface 2019;16(160).
Аннотация: Our 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. © 2019 The Author(s) Published by the Royal Society. All rights reserved.
URI документа: https://elib.bsu.by/handle/123456789/261154
DOI документа: 10.1098/rsif.2019.0536
Scopus идентификатор документа: 85075291442
Финансовая поддержка: This work was supported by the Research Grant Council of Hong Kong (grant no. 25610118), the Hong Kong Polytechnic Univer-sityStart-Up Grant (grant no. 1-BE0J) and the National Research Foundation, Prime Minister?s Office, Singapore, under its CREATE programme, Singapore-MIT Alliance for Research and Technology (SMART) Future Urban Mobility (FM) IRG.1Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong 2Singapore-MIT Alliance for Research and Technology, 1 Create Way, Singapore 3Faculty of Applied Mathematics and Computer Science, Belarusian State University, Minsk, Belarus 4Senseable City Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA 5Istituto di Informatica e Telematica del CNR, Pisa, Italy
Располагается в коллекциях:Статьи

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