Nilforoshan, Hamed and Looi, Wenli and Pierson, Emma and Villanueva, Blanca and Fishman, Nic and Chen, Yiling and Sholar, John and Redbird, Beth and Grusky, David and Leskovec, Jure (2023) Human mobility networks reveal increased segregation in large cities. Nature. ISSN 0028-0836
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Abstract
A long-standing expectation is that large, dense and cosmopolitan areas support socioeconomic mixing and exposure among diverse individuals1,2,3,4,5,6. 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.
Item Type: | Article |
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Subjects: | Universal Eprints > Geological Science |
Depositing User: | Managing Editor |
Date Deposited: | 22 Dec 2023 07:10 |
Last Modified: | 22 Dec 2023 07:10 |
URI: | http://journal.article2publish.com/id/eprint/3472 |