Understanding How People Perceive and Interact with Public Space through Social Media Big Data: A Case Study of Xiamen, China

Shuran Li (), Chengwei Wang, Liying Rong, Shiqi Zhou and Zhiqiang Wu ()
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Shuran Li: College of Design and Innovation, Tongji University, No. 281 Fuxin Road, Yangpu District, Shanghai 200093, China
Chengwei Wang: Future City (Shanghai) Design Consulting Co., Ltd., No. 568 Dalian Road, Yangpu District, Shanghai 200082, China
Liying Rong: Future City (Shanghai) Design Consulting Co., Ltd., No. 568 Dalian Road, Yangpu District, Shanghai 200082, China
Shiqi Zhou: College of Design and Innovation, Tongji University, No. 281 Fuxin Road, Yangpu District, Shanghai 200093, China
Zhiqiang Wu: College of Architecture and Urban Planning, Tongji University, Shanghai 200093, China

Land, 2024, vol. 13, issue 9, 1-27

Abstract: Public space is a crucial forum for public interaction and diverse activities among urban residents. Understanding how people interact with and perceive these spaces is essential for public placemaking. With billions of users engaging in social media expression and generating millions of data points every second, Social Media Big Data (SMBD) offers an invaluable lens for evaluating public spaces over time, surpassing traditional methods like surveys and questionnaires. This research introduces a comprehensive analytical framework that integrates SMBD with placemaking practices, specifically applied to the city of Xiamen, China. The result shows the social sentiment, vibrancy heatmaps, leisure activities, visitor behaviors, and preferred visual elements of Xiamen, offering urban designers valuable insights into the dynamic nature of citizen experiences. The findings underscore the potential of SMBD to inform and enhance public space design, providing a holistic approach to creating more inclusive, vibrant, and functional urban environments.

Keywords: data facilitate design; public space; social media; urban design (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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