---
title: "Mapping Socio-Economic Divides with Urban Mobility Data"
authors: "Yingche Liu; Mengyang Li"
source: "arXiv"
source_url: "https://arxiv.org/abs/2510.08598v1"
paper_id: "2510.08598v1"
harvested: 2026-07-28T18:46:55.172194
keywords: [infranomics, infrastructure_economics, economic_stratification, sovereignty_infrastructure]
pdf_url: "https://arxiv.org/pdf/2510.08598v1.pdf"
---

# Mapping Socio-Economic Divides with Urban Mobility Data

**Authors:** Yingche Liu; Mengyang Li
**Source:** [arXiv](https://arxiv.org/abs/2510.08598v1)
**Paper ID:** 2510.08598v1

## Abstract

The massive digital footprints generated by bike-sharing systems in megacities like Shanghai offer a novel perspective on the urban socio-economic fabric. This study investigates whether these daily mobility patterns can quantitatively map the city's underlying social stratification. To overcome the persistent challenge of acquiring fine-grained socio-economic data, we constructed a multi-layered analytical dataset. We annotated 2,000 raw bike trips with local economic attributes, derived from a novel data enrichment methodology that employs a Large Language Model (LLM), and integrated contextual features of the built environment. A Random Forest model was then utilized as an interpretable framework to determine the key factors governing the relationship between mobility behavior and local economic status. The analysis reveals a compelling and unambiguous finding: a neighborhood's economic level, proxied by housing prices, is the single most dominant predictor of its bike-sharing patterns, substantially outweighing other geographic or temporal factors. This economic determinism manifests in three distinct ways: (1) a spatial clustering of resources, a phenomenon we term the \textit{club effect}, which concentrates mobility infrastructure and usage in affluent areas; (2) a functional dichotomy between necessity-driven, utilitarian usage in lower-income zones and flexible, recreational usage in wealthier ones; and (3) a nuanced inverted U-shaped adoption curve that identifies the urban middle class as the system's primary user base.

## Keywords

infranomics, infrastructure_economics, economic_stratification, sovereignty_infrastructure

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