Latent patterns of urban mixing in mobility analysis across five global cities

• URL: http://arxiv.org/abs/2604.12202v1
• Date: Tue, 14 Apr 2026 02:10:53 GMT
• Title: Latent patterns of urban mixing in mobility analysis across five global cities
• Abstract summary: This studyleverages large-scale travel surveys for over 200,000 residents across Boston, Chicago, Hong Kong, London, and Sao Paulo.<n>With rich individual-level data, we make systematic comparisons and reveal patterns in social mixing, which cannot be identified by analyzing high-resolution mobility data alone.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This study leverages large-scale travel surveys for over 200,000 residents across Boston, Chicago, Hong Kong, London, and Sao Paulo. With rich individual-level data, we make systematic comparisons and reveal patterns in social mixing, which cannot be identified by analyzing high-resolution mobility data alone. Using the same set of data, inferring socioeconomic status from residential neighborhoods yield social mixing levels 16% lower than using self-reported survey data. Besides, individuals over the age of 66 experience greater social mixing than those in late working life (aged 55 to 65), lending data-driven support to the "second youth" hypothesis. Teenagers and women with caregiving responsibilities exhibit lower social mixing levels. Across the five cities, proximity to major transit stations reduces the influence of individual socioeconomic status on social mixing. Finally, we construct detailed spatio-temporal place networks for each city using a graph neural network. Inputs of home-space, activity-space and demographic attributes are embedded and fed into a supervised autoencoder to predict individual exposure vectors. Results show that the structure of individual activity space, i.e., where people travel to, explains most of the variations in place exposure, suggesting that mobility shapes experienced social mixing more than sociodemographic characteristics, home environment, and transit proximity. The ablation tests further discover that, while different income groups may experience similar levels of social mixing, their activity spaces remain stratified by income, resulting in structurally different social mixing experiences.

Related papers

• When Proximity Falls Short: Inequalities in Commuting and Accessibility by Public Transport in Santiago, Chile [0.16385815610837165]
  This study analyzes commuting patterns and accessibility inequalities in Santiago, Chile.<n>Average commuting times remain consistent across socioeconomic groups.<n>Despite residing in areas with greater opportunity density, higher-income populations do not consistently experience shorter commuting times.
  arXiv  Detail & Related papers  (2025-07-29T12:21:56Z)
• Global urban visual perception varies across demographics and personalities [1.3651611781068242]
  We conducted a largescale urban visual perception survey of streetscapes worldwide using street view imagery.<n>We examined how demographics -- including gender, age, income, education, race and ethnicity, and personality traits -- shape perceptions.<n>This dataset reveals demographic- and personality-based differences across six traditional indicators.
  arXiv  Detail & Related papers  (2025-05-19T06:35:11Z)
• InclusiViz: Visual Analytics of Human Mobility Data for Understanding and Mitigating Urban Segregation [41.758626973743525]
  InclusiViz is a novel visual analytics system for multi-level analysis of urban segregation.<n>We developed a deep learning model to predict mobility patterns across social groups using environmental features, augmented with explainable AI.<n>The system integrates innovative visualizations that allow users to explore segregation patterns from broad overviews to fine-grained detail.
  arXiv  Detail & Related papers  (2025-01-07T07:50:36Z)
• Time-space dynamics of income segregation: a case study of Milan's neighbourhoods [0.0]
  We propose a three-dimensional space to analyze social mixing, which is embedded in the temporal dynamics of urban activities. While residential areas fail to encourage social mixing in the nighttime, the working hours foster inclusion, with the city center showing a heightened level of interaction. leisure areas emerge as potential facilitators for social interactions, depending on urban features such as public transport and a variety of Points Of Interest.
  arXiv  Detail & Related papers  (2023-09-29T14:50:13Z)
• Flexible social inference facilitates targeted social learning when rewards are not observable [58.762004496858836]
  Groups coordinate more effectively when individuals are able to learn from others' successes. We suggest that social inference capacities may help bridge this gap, allowing individuals to update their beliefs about others' underlying knowledge and success from observable trajectories of behavior.
  arXiv  Detail & Related papers  (2022-12-01T21:04:03Z)
• Identifying latent activity behaviors and lifestyles using mobility data to describe urban dynamics [3.8424737607413153]
  Digitally acquired data can accurately capture complex human activity, but it lacks the interpretability of demographic data. We use a privacy-enhanced dataset of mobility visitation patterns of 1.2 million people to 1.1 million places in 11 metro areas in the U.S. We find lifestyles can be automatically decomposed into only 12 latent interpretable activity behaviors on how people combine shopping, eating, working, or using their free time.
  arXiv  Detail & Related papers  (2022-09-24T22:08:51Z)
• This Must Be the Place: Predicting Engagement of Online Communities in a Large-scale Distributed Campaign [70.69387048368849]
  We study the behavior of communities with millions of active members. We develop a hybrid model, combining textual cues, community meta-data, and structural properties. We demonstrate the applicability of our model through Reddit's r/place a large-scale online experiment.
  arXiv  Detail & Related papers  (2022-01-14T08:23:16Z)
• Two-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality Profiling [74.83957286553924]
  We infer the Myers-Briggs Personality Type indicators by applying a novel multi-view fusion framework, called "PERS" Our experimental results demonstrate the PERS's ability to learn from multi-view data for personality profiling by efficiently leveraging on the significantly different data arriving from diverse social multimedia sources.
  arXiv  Detail & Related papers  (2021-06-20T10:48:49Z)
• Entropy as a measure of attractiveness and socioeconomic complexity in Rio de Janeiro metropolitan area [52.77024349608834]
  We use a mobile phone dataset and an entropy-based metric to measure the attractiveness of a location. The results show that the attractiveness of a given location measured by entropy is an important descriptor of the socioeconomic status of the location.
  arXiv  Detail & Related papers  (2020-03-23T15:58:56Z)
• Measuring Spatial Subdivisions in Urban Mobility with Mobile Phone Data [58.720142291102135]
  By 2050 two thirds of the world population will reside in urban areas. This growth is faster and more complex than the ability of cities to measure and plan for their sustainability. To understand what makes a city inclusive for all, we define a methodology to identify and characterize spatial subdivisions.
  arXiv  Detail & Related papers  (2020-02-20T14:37:46Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.