A Semantic Analysis Method of Public Public Built Environment and Its Landscape Based on Big Data Technology: Kimbell Art Museum as Example

Zhongzhong Zeng (), Meizhu Wang, Dingyi Liu, Xuan Yu and Bo Zhang
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Zhongzhong Zeng: School of Architecture and Design, Beijing Jiaotong University, Beijing 100080, China
Meizhu Wang: School of Architecture and Design, Beijing Jiaotong University, Beijing 100080, China
Dingyi Liu: School of Architecture and Design, Beijing Jiaotong University, Beijing 100080, China
Xuan Yu: School of Architecture and Design, Beijing Jiaotong University, Beijing 100080, China
Bo Zhang: Horticulture and Landscape Architecture Department, Oklahoma State University, Stillwater, OK 74078-1015, USA

Land, 2024, vol. 13, issue 5, 1-16

Abstract: Based on big data, a new public space evaluation method is proposed. Using programming technology to collect visitor reviews from the travel website TripAdvisor to build a database, based on the data of 99,240 words in 1573 visitor reviews in 10 years, the connection between data and reality is established through systematic data classification and visualization. Following an assessment of the Kimbell Art Museum’s functionality, architectural design, and landscape design, along with visitor feedback, a new evaluation methodology was formulated for application to public buildings with landscapes. By utilizing the unique advantages of big data, it provides convenient and efficient analysis methods for public spaces with similar data foundations and opens the way for the optimization of the built environment in the information age.

Keywords: space evaluation method; big data mining; public architecture evaluation; Kimbell Art Museum (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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