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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