期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2018
卷号：115
期号：30
页码：7735-7740
DOI：10.1073/pnas.1802537115
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：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.
关键词：race ; neighborhood ; social isolation ; urban mobility ; big data
