Nolan E. Phillips, Brian L. Levy, Robert J. Sampson, Mario L. Small & Ryan Q. Wang
Phillips, N. E. , Levy, B. L. , Sampson, R. J. , Small, M. L. & Wang, R. Q. (2019). The Social Integration of American Cities: Network Measures of Connectedness Based on Everyday Mobility Across Neighborhoods. Sociological Methods & Research, 004912411985238. http://dx.doi.org/10.1177/0049124119852386
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.
This article states that opportunities for contact are necessary to the social integration of a city and these opportunities rely on daily mobility patterns across different neighborhoods. Social integration and structural connectedness are linked by the extent to which people can interact with residents of different neighborhoods. Structural connectedness is defined as the degree to which the residents’ movements connect neighborhoods. The authors developed the EMI (equitable mobility index) and the CMI (concentrated mobility index) to measure a city’s structural connectedness. The EMI measures the extent to which neighborhoods visit others in equal proportions while the CMI measures the degree to which travels are concentrated to a handful of receiving neighborhoods. The correlation between the CMI and EMI was found to be -0.033, meaning the two measures each show distinct features of the structural connectedness of a city's mobility networks. Large cities display a small EMI, due to the difficulty of visiting all neighborhoods of a large city, while there was no significant correlation for city size and CMI. The structural connectedness of cities was often found to rely on neighborhood hot spots, e.g., public spaces like Grand Central Terminal in New York City, or Grant Park in Chicago.
Description of method used in the article
The measures were applied to a data set of 650 million geocoded tweets from 1.3 million Twitter users sent from October, 2013, to March, 2015. Fifty US cities, including New York, San Francisco, Detroit, and Miami, were examined in this study.
Of some practical use if combined with other research