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Human mobility networks reveal increased segregation in large cities

Author

Listed:
  • Hamed Nilforoshan

    (Stanford University)

  • Wenli Looi

    (Stanford University)

  • Emma Pierson

    (Cornell Tech)

  • Blanca Villanueva

    (Stanford University)

  • Nic Fishman

    (Stanford University)

  • Yiling Chen

    (Stanford University)

  • John Sholar

    (Stanford University)

  • Beth Redbird

    (Northwestern University
    Northwestern University)

  • David Grusky

    (Stanford University)

  • Jure Leskovec

    (Stanford University)

Abstract

A long-standing expectation is that large, dense and cosmopolitan areas support socioeconomic mixing and exposure among diverse individuals1–6. Assessing this hypothesis has been difficult because previous measures of socioeconomic mixing have relied on static residential housing data rather than real-life exposures among people at work, in places of leisure and in home neighbourhoods7,8. Here we develop a measure of exposure segregation that captures the socioeconomic diversity of these everyday encounters. Using mobile phone mobility data to represent 1.6 billion real-world exposures among 9.6 million people in the United States, we measure exposure segregation across 382 metropolitan statistical areas (MSAs) and 2,829 counties. We find that exposure segregation is 67% higher in the ten largest MSAs than in small MSAs with fewer than 100,000 residents. This means that, contrary to expectations, residents of large cosmopolitan areas have less exposure to a socioeconomically diverse range of individuals. Second, we find that the increased socioeconomic segregation in large cities arises because they offer a greater choice of differentiated spaces targeted to specific socioeconomic groups. Third, we find that this segregation-increasing effect is countered when a city’s hubs (such as shopping centres) are positioned to bridge diverse neighbourhoods and therefore attract people of all socioeconomic statuses. Our findings challenge a long-standing conjecture in human geography and highlight how urban design can both prevent and facilitate encounters among diverse individuals.

Suggested Citation

  • Hamed Nilforoshan & Wenli Looi & Emma Pierson & Blanca Villanueva & Nic Fishman & Yiling Chen & John Sholar & Beth Redbird & David Grusky & Jure Leskovec, 2023. "Human mobility networks reveal increased segregation in large cities," Nature, Nature, vol. 624(7992), pages 586-592, December.
  • Handle: RePEc:nat:nature:v:624:y:2023:i:7992:d:10.1038_s41586-023-06757-3
    DOI: 10.1038/s41586-023-06757-3
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    Citations

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    Cited by:

    1. Wenmei Wu & Shenzhen Tian & Hang Li & Xueming Li & Yadan Wang, 2024. "Multi-Source Data-Based Investigation of Spatiotemporal Heterogeneity and Driving Mechanisms of Coupling and Coordination in Human Settlements in Urban Agglomeration in the Middle Reaches of the Yangt," Sustainability, MDPI, vol. 16(17), pages 1-26, September.
    2. Kaixin Zhu & Zhifeng Cheng & Jianghao Wang, 2024. "Measuring Chinese mobility behaviour during COVID-19 using geotagged social media data," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    3. Becky P. Y. Loo & Zhuangyuan Fan & Esteban Moro, 2024. "Residential and experienced social segregation: the roles of different transport modes, metro extensions, and longitudinal changes in Hong Kong," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.

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