Evidence map›Paper›PMID 31744420›Full record

ArticleJournal of the Royal Society, Interface2019

Quantifying segregation in an integrated urban physical-social space.

Yang Xu, Alexander Belyi, Paolo Santi, Carlo Ratti

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Urban highways are barriers to social ties.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Article
  7. Socioeconomic reorganization of communication and mobility networks in response to external shocks.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yang XuDepartment of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Alexander BelyiSingapore-MIT Alliance for Research and Technology, 1 Create Way, Singapore.
Paolo SantiSenseable City Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Carlo RattiSenseable City Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Models, TheoreticalSocial ClassSocial EnvironmentSocial SegregationUrban PopulationCitiesHumansSingaporebig data analyticshomophilymobile phone datasocial networksocial segregationurban mobility

Identifiers

PMID31744420
PMCPMC6893495

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.