Socioeconomic biases in urban mixing patterns of US metropolitan areas
Department of Network and Data Science, Central European University, 1100, Vienna, Austria
2 Department of Computer Science, Aalto University School of Science, 00076, Aalto, Finland
3 Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 04510, Ciudad de México, Mexico
4 Alfréd Rényi Institute of Mathematics, 1053, Budapest, Hungary
Accepted: 25 April 2022
Published online: 23 May 2022
Urban areas serve as melting pots of people with diverse socioeconomic backgrounds, who may not only be segregated but have characteristic mobility patterns in the city. While mobility is driven by individual needs and preferences, the specific choice of venues to visit is usually constrained by the socioeconomic status of people. The complex interplay between people and places they visit, given their personal attributes and homophily leaning, is a key mechanism behind the emergence of socioeconomic stratification patterns ultimately leading to urban segregation at large. Here we investigate mixing patterns of mobility in the twenty largest cities of the United States by coupling individual check-in data from the social location platform Foursquare with census information from the American Community Survey. We find strong signs of stratification indicating that people mostly visit places in their own socioeconomic class, occasionally visiting locations from higher classes. The intensity of this ‘upwards bias’ increases with socioeconomic status and correlates with standard measures of racial residential segregation. Our results suggest an even stronger socioeconomic segregation in individual mobility than one would expect from system-level distributions, shedding further light on uneven mobility mixing patterns in cities.
Key words: Segregation in mobility / Urban mixing / Socioeconomic inequalities
© The Author(s) 2022
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