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Understanding neighborhood income segregation around the clock using mobile phone ambient population data

Sociology

Understanding neighborhood income segregation around the clock using mobile phone ambient population data

L. Cai, G. Song, et al.

This groundbreaking study by Liang Cai, Guangwen Song, and Yanji Zhang explores the intriguing dynamics of income segregation in Guangzhou, China, utilizing innovative mobile phone data. Discover how urban functions and neighborhood characteristics shape daily segregation patterns in an engaging way.

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Playback language: English
Abstract
This study investigates the temporal dynamics of income segregation in Guangzhou, China, using mobile phone data. It employs ordinal entropy to measure segregation among eight income groups within 400m urban grids over a weekday and weekend. The study decomposes segregation by location and time, identifying the role of urban functions (retail, accommodation, offices) and neighborhood characteristics (residents, non-local migrants). Group-based trajectory analysis reveals distinct daily segregation patterns, highlighting the enduring nature of neighborhood income segregation and its real-time responsiveness to contextual influences.
Publisher
Humanities and Social Sciences Communications
Published On
Feb 29, 2024
Authors
Liang Cai, Guangwen Song, Yanji Zhang
Tags
income segregation
Guangzhou
mobile phone data
urban dynamics
neighborhood characteristics
segregation patterns
ordinal entropy

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