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      Urban mobility and neighborhood isolation in America’s 50 largest cities

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          Significance

          Living in disadvantaged neighborhoods is widely assumed to undermine life chances because residents are isolated from neighborhoods with greater resources. Yet, residential isolation may be mitigated by individuals spending much of their everyday lives outside their home neighborhoods, a possibility that has been difficult to assess on a large scale. Using new methods to analyze urban mobility in the 50 largest American cities, we find that residents of primarily black and Hispanic neighborhoods—whether poor or not—are far less exposed to either nonpoor or white middle-class neighborhoods than residents of primarily white neighborhoods. Although residents of disadvantaged neighborhoods regularly travel as far and to as many different neighborhoods as those from advantaged neighborhoods, their relative isolation and segregation persist.

          Abstract

          Influential research on the negative effects of living in a disadvantaged neighborhood assumes that its residents are socially isolated from nonpoor or “mainstream” neighborhoods, but the extent and nature of such isolation remain in question. We develop a test of neighborhood isolation that improves on static measures derived from commonly used census reports by leveraging fine-grained dynamic data on the everyday movement of residents in America’s 50 largest cities. We analyze 650 million geocoded Twitter messages to estimate the home locations and travel patterns of almost 400,000 residents over 18 mo. We find surprisingly high consistency across neighborhoods of different race and income characteristics in the average travel distance (radius) and number of neighborhoods traveled to (spread) in the metropolitan region; however, we uncover notable differences in the composition of the neighborhoods visited. Residents of primarily black and Hispanic neighborhoods—whether poor or not—are far less exposed to either nonpoor or white middle-class neighborhoods than residents of primarily white neighborhoods. These large racial differences are notable given recent declines in segregation and the increasing diversity of American cities. We also find that white poor neighborhoods are substantially isolated from nonpoor white neighborhoods. The results suggest that even though residents of disadvantaged neighborhoods travel far and wide, their relative isolation and segregation persist.

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          Most cited references51

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          Understanding individual human mobility patterns

          Despite their importance for urban planning, traffic forecasting, and the spread of biological and mobile viruses, our understanding of the basic laws governing human motion remains limited thanks to the lack of tools to monitor the time resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six month period. We find that in contrast with the random trajectories predicted by the prevailing Levy flight and random walk models, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time independent characteristic length scale and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent based modeling.
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            Great American City

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              The Truly Disadvantaged

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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                24 July 2018
                9 July 2018
                9 July 2018
                : 115
                : 30
                : 7735-7740
                Affiliations
                [1] aDepartment of Civil and Environmental Engineering, Northeastern University , Boston, MA 02115;
                [2] bDepartment of Sociology, Harvard University , Cambridge, MA 02138
                Author notes
                1To whom correspondence should be addressed. Email: q.wang@ 123456northeastern.edu .

                Edited by Douglas S. Massey, Princeton University, Princeton, NJ, and approved June 6, 2018 (received for review February 10, 2018)

                Author contributions: Q.W., N.E.P., M.L.S., and R.J.S. designed research; Q.W., N.E.P., M.L.S., and R.J.S. performed research; Q.W., N.E.P., and R.J.S. analyzed data; and Q.W., N.E.P., M.L.S., and R.J.S. wrote the paper.

                Article
                201802537
                10.1073/pnas.1802537115
                6065036
                29987019
                e6d7c851-3381-42dd-84a6-c14d75f1a8f1
                Copyright © 2018 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                Page count
                Pages: 6
                Funding
                Funded by: John D. and Catherine T. MacArthur Foundation (MacArthur Foundation) 100000870
                Award ID: 14-107644-000-USP
                Award Recipient : Mario L. Small Award Recipient : Robert J. Sampson
                Funded by: National Science Foundation (NSF) 100000001
                Award ID: SES-1637136
                Award Recipient : Mario L. Small Award Recipient : Robert J. Sampson
                Categories
                Social Sciences
                Social Sciences

                race,neighborhood,social isolation,urban mobility,big data
                race, neighborhood, social isolation, urban mobility, big data

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