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We Are What We Buy: Extracting urban lifestyles using large-scale delivery records

We Are What We Buy: Extracting urban lifestyles using large-scale delivery records

来源:Arxiv_logoArxiv
英文摘要

Lifestyle has been used as a lens to characterize a society and its people within, which includes their social status, consumption habits, values, and cultural interests. Recently, the increasing availability of large-scale purchasing records, such as credit card transaction data, has enabled data-driven studies to capture lifestyles through consumption behavior. However, the lack of detailed information on individual purchases prevents researchers from constructing a precise representation of lifestyle structures through the consumption pattern. Here, we extract urban lifestyle patterns as a composition of fine-grained product categories that are significantly consumed together. Leveraging 103,342,186 package delivery records from 2018 to 2022 in Seoul, Republic of Korea, we construct a co-consumption network of detailed product categories and systematically identify lifestyles as clusters in the network. Our results reveal five lifestyle clusters: 'Beauty lovers', 'Fashion lovers', 'Work and life', 'Homemakers', and 'Baby and hobbyists', which represent distinctive lifestyles while also being connected to each other. Moreover, the geospatial distribution of lifestyle clusters aligns with regional characteristics (business vs. residential areas) and is associated with multiple demographic characteristics of residents, such as income, birth rate, and age. Temporal analysis further demonstrates that lifestyle patterns evolve in response to external disruptions, such as COVID-19. As urban societies become more multifaceted, our framework provides a powerful tool for researchers, policymakers, and businesses to understand the shifting dynamics of contemporary lifestyles.

Minjin Lee、Hokyun Kim、Bogang Jun、Jaehyuk Park

信息传播、知识传播科学、科学研究

Minjin Lee,Hokyun Kim,Bogang Jun,Jaehyuk Park.We Are What We Buy: Extracting urban lifestyles using large-scale delivery records[EB/OL].(2025-04-22)[2025-05-25].https://arxiv.org/abs/2504.15618.点此复制

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