Time-space dynamics of income segregation in the city of Milan

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Abstract

Traditional approaches to urban income segregation focus on static residential patterns, often failing to capture the dynamic nature of social mixing at the neighborhood level. We leverage high-resolution location-based data from mobile phones to capture the interplay of three different income groups (high, medium, and low) based on their daily routines. The three income groups define a novel 3D space embedded in the temporal dynamics of urban activities, which we propose as a framework to analyze social mixing. This framework offers a more detailed perspective on social interactions, closely linked to the geographical features of each neighborhood. While nighttime residential patterns show high segregation, the working hours foster inclusion, with the city center showing heightened levels of interaction. As evening sets in, leisure areas emerge as potential facilitators for social interactions, depending on urban features such as public transport and various Points Of Interest. These characteristics significantly modulate the magnitude and type of social stratification involved in social mixing, underscoring the significance of urban design in bridging or widening socio-economic divides.

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APA

Rossi Mori, L., Loreto, V., & Di Clemente, R. (2025). Time-space dynamics of income segregation in the city of Milan. PNAS Nexus, 4(9). https://doi.org/10.1093/pnasnexus/pgaf283

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