We use anonymized and aggregated data from Facebook to explore the spatial structure of social networks in the New York metro area. We highlight the importance of transportation infrastructure in shaping urban social networks by showing that travel time and travel costs are substantially stronger predictors of social connectedness between zip codes than geographic distance is. We also document significant heterogeneity in the geographic breadth of social networks across New York zip codes, and show that much of this heterogeneity is explained by the ease of access to public transit, even after controlling for socioeconomic characteristics of the zip codes’ residents. When we group zip codes with strong social ties into hypothetical communities using an agglomerative clustering algorithm, we find that geographically non-contiguous locations are grouped into socially connected communities, again highlighting that geographic distance is an imperfect proxy for urban social connectedness. We also explore the social connections between New York zip codes and foreign countries, and highlight how these are related to past migration movements.
Michael Bailey, Patrick Farrell, Theresa Kuchler, and Johannes Stroebel