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Urban Commercial Space Vitality Evaluation Method Based on Social Media Data: The Case of Shanghai

Author

Listed:
  • Yuwen Zhang

    (School of Geographic Sciences, East China Normal University, Shanghai 200241, China)

  • Mingfeng Wang

    (School of Geographic Sciences, East China Normal University, Shanghai 200241, China
    Research Center for China Administrative Division, East China Normal University, Shanghai 200241, China)

  • Xinyu Yang

    (School of Geographic Sciences, East China Normal University, Shanghai 200241, China)

  • Ruixuan Zhang

    (School of Geographic Sciences, East China Normal University, Shanghai 200241, China)

Abstract

Social media has rapidly intervened in the interaction between urban consumers and commercial space, further reshaping the structure of urban commercial space. This study employed the social, spatial, and subjective dimensions of geographies of consumption as the theoretical framework. Based on the data from five social media platforms, including Douyin, REDnote, Weibo, Dianping, and Baidu Index, we constructed a multi-level evaluation method of “attention level–activity degree–experience quality” and applied it to measure the dynamics of the shopping malls in Shanghai to investigate their mechanism of generating urban commercial space vitality. The findings indicate that the “core + core–periphery + multi-center + circle structure, agglomeration, and balance” is the primary pattern of urban commercial space in Shanghai. The differences in business formats, consumer positioning, and consumption culture revealed by the social media data are conducive to clarifying the scale of the regional consumption space and the logic of urban commercial evolution. The main contribution of this study is the demonstration that this evaluation method rooted in social media has the potential to generalize the measurement of urban commercial space in major cities in China. We also propose corresponding countermeasures and suggestions for developing urban commercial space in Shanghai.

Suggested Citation

  • Yuwen Zhang & Mingfeng Wang & Xinyu Yang & Ruixuan Zhang, 2025. "Urban Commercial Space Vitality Evaluation Method Based on Social Media Data: The Case of Shanghai," Land, MDPI, vol. 14(4), pages 1-25, March.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:4:p:697-:d:1620129
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    References listed on IDEAS

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    1. Turgut Acikara & Bo Xia & Tan Yigitcanlar & Carol Hon, 2023. "Contribution of Social Media Analytics to Disaster Response Effectiveness: A Systematic Review of the Literature," Sustainability, MDPI, vol. 15(11), pages 1-50, May.
    2. Ruibin Zhou & Chenshuo Wang & Dongting Bao & Xiaolan Xu, 2024. "Shopping Mall Site Selection Based on Consumer Behavior Changes in the New Retail Era," Land, MDPI, vol. 13(6), pages 1-21, June.
    3. Yuanyuan Huang & Bohong Zheng, 2024. "Social Media Users’ Visual and Emotional Preferences of Internet-Famous Sites in Urban Riverfront Public Spaces: A Case Study in Changsha, China," Land, MDPI, vol. 13(7), pages 1-32, June.
    4. Shujuan Li & Bo Yang, 2022. "Social media for landscape planning and design: a review and discussion," Landscape Research, Taylor & Francis Journals, vol. 47(5), pages 648-663, July.
    5. Wei Liu & Dong Li & Yuan Meng & Chuanmin Guo, 2024. "The Relationship between Emotional Perception and High-Density Built Environment Based on Social Media Data: Evidence from Spatial Analyses in Wuhan," Land, MDPI, vol. 13(3), pages 1-24, February.
    6. Bhimani, Hardik & Mention, Anne-Laure & Barlatier, Pierre-Jean, 2019. "Social media and innovation: A systematic literature review and future research directions," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 251-269.
    7. Bianca E. Lopez & Nicholas R. Magliocca & Andrew T. Crooks, 2019. "Challenges and Opportunities of Social Media Data for Socio-Environmental Systems Research," Land, MDPI, vol. 8(7), pages 1-18, July.
    8. Indaco, Agustín, 2020. "From twitter to GDP: Estimating economic activity from social media," Regional Science and Urban Economics, Elsevier, vol. 85(C).
    9. Gabriele Zabelskyte & Nadja Kabisch & Zaneta Stasiskiene, 2022. "Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review," Land, MDPI, vol. 11(2), pages 1-21, February.
    10. Jingyuan Zhang & Jusheng Song & Zouyang Fan, 2023. "The Study of Historical Progression in the Distribution of Urban Commercial Space Locations—Example of Paris," Sustainability, MDPI, vol. 15(19), pages 1-23, October.
    11. Ardaman Kaur & André Leite Rodrigues & Sarah Hoogstraten & Diego Andrés Blanco-Mora & Bruno Miranda & Paulo Morgado & Dar Meshi, 2023. "An Urban Image Stimulus Set Generated from Social Media," Data, MDPI, vol. 8(12), pages 1-12, December.
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