IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v50y2021i3p1110-1149.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124119852386
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0049124119852386?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Wilson, William Julius, 2012. "The Truly Disadvantaged," University of Chicago Press Economics Books, University of Chicago Press, edition 2, number 9780226901268, September.
    2. 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).
    3. 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.
    4. 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.
    5. 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).
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cody J. Dey & James S. Quinn, 2014. "Individual attributes and self-organizational processes affect dominance network structure in pukeko," Behavioral Ecology, International Society for Behavioral Ecology, vol. 25(6), pages 1402-1408.
    2. Fei Li & Donggen Wang, 2017. "Measuring urban segregation based on individuals’ daily activity patterns: A multidimensional approach," Environment and Planning A, , vol. 49(2), pages 467-486, February.
    3. Goodreau, Steven M. & Handcock, Mark S. & Hunter, David R. & Butts, Carter T. & Morris, Martina, 2008. "A statnet Tutorial," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i09).
    4. Lee Fiorio & Emilio Zagheni & Guy L. Abel & Johnathan Hill & Gabriel Pestre & Emmanuel Letouzé & Jixuan Cai, 2020. "Analyzing the effect of time in migration measurement using geo-referenced digital trace data," MPIDR Working Papers WP-2020-024, Max Planck Institute for Demographic Research, Rostock, Germany.
    5. Angel Ortiz-Pelaez & Getaneh Ashenafi & Francois Roger & Agnes Waret-Szkuta, 2012. "Can Geographical Factors Determine the Choices of Farmers in the Ethiopian Highlands to Trade in Livestock Markets?," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-11, February.
    6. Naomi F. Sugie & Michael C. Lens, 2017. "Daytime Locations in Spatial Mismatch: Job Accessibility and Employment at Reentry From Prison," Demography, Springer;Population Association of America (PAA), vol. 54(2), pages 775-800, April.
    7. Zhang, Yanji & Wang, Jiejing & Kan, Changcheng, 2022. "Temporal variation in activity-space-based segregation: A case study of Beijing using location-based service data," Journal of Transport Geography, Elsevier, vol. 98(C).
    8. Shen, Yao, 2019. "Segregation through space: A scope of the flow-based spatial interaction model," Journal of Transport Geography, Elsevier, vol. 76(C), pages 10-23.
    9. Wenfei Xu, 2022. "The contingency of neighbourhood diversity: Variation of social context using mobile phone application data," Urban Studies, Urban Studies Journal Limited, vol. 59(4), pages 851-869, March.
    10. Taedong Lee & Susan Meene, 2012. "Who teaches and who learns? Policy learning through the C40 cities climate network," Policy Sciences, Springer;Society of Policy Sciences, vol. 45(3), pages 199-220, September.
    11. Hunter, David R. & Goodreau, Steven M. & Handcock, Mark S., 2013. "ergm.userterms: A Template Package for Extending statnet," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i02).
    12. Abbasi, Sorath & Ko, Joonho & Min, Jaehong, 2021. "Measuring destination-based segregation through mobility patterns: Application of transport card data," Journal of Transport Geography, Elsevier, vol. 92(C).
    13. Alex Stivala & Garry Robins & Alessandro Lomi, 2020. "Exponential random graph model parameter estimation for very large directed networks," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-21, January.
    14. Jennifer Candipan & Nolan Edward Phillips & Robert J Sampson & Mario Small, 2021. "From residence to movement: The nature of racial segregation in everyday urban mobility," Urban Studies, Urban Studies Journal Limited, vol. 58(15), pages 3095-3117, November.
    15. Yonghong Ma & Xiaomeng Yang & Sen Qu & Lingkai Kong, 2022. "Research on the formation mechanism of big data technology cooperation networks: empirical evidence from China," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1273-1294, March.
    16. Epskamp, Sacha & Cramer, Angélique O.J. & Waldorp, Lourens J. & Schmittmann, Verena D. & Borsboom, Denny, 2012. "qgraph: Network Visualizations of Relationships in Psychometric Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i04).
    17. S. M. Mniszewski & S. Y. Del Valle & P. D. Stroud & J. M. Riese & S. J. Sydoriak, 2008. "Pandemic simulation of antivirals + school closures: buying time until strain-specific vaccine is available," Computational and Mathematical Organization Theory, Springer, vol. 14(3), pages 209-221, September.
    18. Moeliono, Moira & Brockhaus, Maria & Gallemore, Caleb & Dwisatrio, Bimo & Maharani, Cynthia D. & Muharrom, Efrian & Pham, Thuy Thu, 2020. "REDD+ in Indonesia: A new mode of governance or just another project?," Forest Policy and Economics, Elsevier, vol. 121(C).
    19. Floriana Gargiulo & Sônia Ternes & Sylvie Huet & Guillaume Deffuant, 2010. "An Iterative Approach for Generating Statistically Realistic Populations of Households," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-9, January.
    20. Teruhiko Yoneyama & Sanmay Das & Mukkai Krishnamoorthy, 2012. "A Hybrid Model for Disease Spread and an Application to the SARS Pandemic," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-5.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:somere:v:50:y:2021:i:3:p:1110-1149. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.