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The Social Integration of American Cities: Network Measures of Connectedness Based on Everyday Mobility Across Neighborhoods

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  • Nolan E. Phillips
  • Brian L. Levy
  • Robert J. Sampson
  • Mario L. Small
  • Ryan Q. Wang

Abstract

The social integration of a city depends on the extent to which people from different neighborhoods have the opportunity to interact with one another, but most prior work has not developed formal ways of conceptualizing and measuring this kind of connectedness. In this article, we develop original, network-based measures of what we call “structural connectedness†based on the everyday travel of people across neighborhoods. Our principal index captures the extent to which residents in each neighborhood of a city travel to all other neighborhoods in equal proportion. Our secondary index captures the extent to which travels within a city are concentrated in a handful of receiving neighborhoods. We illustrate the value of our indices for the 50 largest American cities based on hundreds of millions of geotagged tweets over 18 months. We uncover important features of major American cities, including the extent to which their connectedness depends on a few neighborhood hubs, and the fact that in several cities, contact between some neighborhoods is all but nonexistent. We also show that cities with greater population densities, more cosmopolitanism, and less racial segregation have higher levels of structural connectedness. Our indices can be applied to data at any spatial scale, and our measures pave the way for more powerful and precise analyses of structural connectedness and its effects across a broad array of social phenomena.

Suggested Citation

  • Nolan E. Phillips & Brian L. Levy & Robert J. Sampson & Mario L. Small & Ryan Q. Wang, 2021. "The Social Integration of American Cities: Network Measures of Connectedness Based on Everyday Mobility Across Neighborhoods," Sociological Methods & Research, , vol. 50(3), pages 1110-1149, August.
  • Handle: RePEc:sae:somere:v:50:y:2021:i:3:p:1110-1149
    DOI: 10.1177/0049124119852386
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    References listed on IDEAS

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    1. Wilson, William Julius, 2012. "The Truly Disadvantaged," University of Chicago Press Economics Books, University of Chicago Press, edition 2, number 9780226901268, October.
    2. Malia Jones & Anne Pebley, 2014. "Redefining Neighborhoods Using Common Destinations: Social Characteristics of Activity Spaces and Home Census Tracts Compared," Demography, Springer;Population Association of America (PAA), vol. 51(3), pages 727-752, June.
    3. Hunter, David R. & Handcock, Mark S. & Butts, Carter T. & Goodreau, Steven M. & Morris, Martina, 2008. "ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i03).
    4. Handcock, Mark S. & Hunter, David R. & Butts, Carter T. & Goodreau, Steven M. & Morris, Martina, 2008. "statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i01).
    5. John Palmer & Thomas Espenshade & Frederic Bartumeus & Chang Chung & Necati Ozgencil & Kathleen Li, 2013. "New Approaches to Human Mobility: Using Mobile Phones for Demographic Research," Demography, Springer;Population Association of America (PAA), vol. 50(3), pages 1105-1128, June.
    6. Le Roux, Guillaume & Vallée, Julie & Commenges, Hadrien, 2017. "Social segregation around the clock in the Paris region (France)," Journal of Transport Geography, Elsevier, vol. 59(C), pages 134-145.
    7. Vittoria Colizza & Alain Barrat & Marc Barthelemy & Alain-Jacques Valleron & Alessandro Vespignani, 2007. "Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions," PLOS Medicine, Public Library of Science, vol. 4(1), pages 1-16, January.
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    Cited by:

    1. Aynaz Lotfata & George Grekousis & Ruoyu Wang, 2023. "Using geographical random forest models to explore spatial patterns in the neighborhood determinants of hypertension prevalence across chicago, illinois, USA," Environment and Planning B, , vol. 50(9), pages 2376-2393, November.
    2. Hae Young Yun & Hyun-ah Kwon, 2023. "Neighborhood Identity Formation and the Changes in an Urban Regeneration Neighborhood in Gwangju, Korea," Sustainability, MDPI, vol. 15(15), pages 1-27, July.

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