Deconstructing Mobility Segregation: A Network Analysis of Racialized Flows in Pandemic-Era NYC

TL;DR

This study analyzes racialized mobility patterns in NYC during the pandemic using network analysis, revealing persistent segregation, active homophily, and the impact of COVID-19 restrictions on minority communities.

Contribution

It introduces a dual-metric framework and a Homophily Gravity Model to better understand and predict racial mobility segregation beyond residential patterns.

Findings

Racial flows are predominantly intra-group with 69.27% within-group movements.

Active homophily persists across all racial groups after adjusting for spatial factors.

Pandemic restrictions intensified racial isolation, especially for minority communities.

Abstract

Urban segregation research has long relied on residential patterns, yet growing evidence suggests that racial/ethnic segregation also manifests systematically in mobility behaviors. Leveraging anonymized mobile device data from New York City before and during the COVID-19 pandemic, we develop a network-analytic framework to dissect mobility segregation in racialized flow networks. We examine citywide racial mixing patterns through mixing matrices and assortativity indices, revealing persistent diagonal dominance where intra-group flows constituted 69.27% of total movements. Crucially, we develop a novel dual-metric framework that reconceptualizes mobility segregation as two interlocking dimensions: structural segregation-passive exposure patterns driven by residential clustering, and preferential segregation-active homophily in mobility choices beyond spatial constraints. Our gravity-adjusted indices reveal that racial divisions transcend residential clustering-all racial groups exhibit active homophily after spatial adjustments, with particularly severe isolation during the pandemic. Findings highlight how pandemic restrictions disproportionately amplified asymmetric isolation, with minority communities experiencing steeper declines in access to White-dominated spaces. Finally, we propose a Homophily Gravity Model with racial similarity parameter, which significantly improves the prediction accuracy of race-specific mobility flows and more accurately reproduces intra-group mobility preferences and directional exposure patterns.Overall, this study redefines mobility segregation as a multidimensional phenomenon, where structural constraints, active preferences, and crisis responses compound to reshape urban racial inequality.