AI RESEARCH
Latent patterns of urban mixing in mobility analysis across five global cities
arXiv CS.AI
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ArXi:2604.12202v1 Announce Type: new 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.