Li, Q.-Q. and Yue, Y. and Gao, Q.-L. and Zhong, C. and Barros, Joana (2022) Towards a new paradigm for segregation measurement in an era of big data. Urban Informatics 1 (5), ISSN 2731-6963.
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Abstract
Recent theoretical and methodological advances in activity space and big data provide new opportunities to study socio-spatial segregation. This review first provides an overview of the literature in terms of measurements, spatial patterns, underlying causes, and social consequences of spatial segregation. These studies are mainly place-centred and static, ignoring the segregation experience across various activity spaces due to the dynamism of movements. In response to this challenge, we highlight the work in progress toward a new paradigm for segregation studies. Specifically, this review presents how and the extent to which activity space methods can advance segregation research from a people-based perspective. It explains the requirements of mobility-based methods for quantifying the dynamics of segregation due to high movement within the urban context. It then discusses and illustrates a dynamic and multi-dimensional framework to show how big data can enhance understanding segregation by capturing individuals’ spatio-temporal behaviours. The review closes with new directions and challenges for segregation research using big data.
Metadata
| Item Type: | Article |
|---|---|
| Keyword(s) / Subject(s): | Inequality, Social segregation, Big data, Activity space, Human mobility |
| School: | Birkbeck Faculties and Schools > Faculty of Humanities and Social Sciences > School of Social Sciences |
| Depositing User: | Joana Barros |
| Date Deposited: | 13 Sep 2022 09:31 |
| Last Modified: | 26 Oct 2023 15:18 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/48888 |
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