Text Mining Applications in the Construction Industry: Current Status, Research Gaps, and Prospects

Na Xu, Xueqing Zhou (), Chaoran Guo, Bai Xiao, Fei Wei and Yuting Hu
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Na Xu: School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221008, China
Xueqing Zhou: School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221008, China
Chaoran Guo: School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221008, China
Bai Xiao: Tianjin Jingang Construction Co., Ltd., Tianjin 300456, China
Fei Wei: Tianjin Jingang Construction Co., Ltd., Tianjin 300456, China
Yuting Hu: School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221008, China

Sustainability, 2022, vol. 14, issue 24, 1-29

Abstract: With the advent of the Industry 4.0 era, information technology has been widely developed and applied in the construction engineering field. Text mining techniques can extract interesting and important data hidden in plain text, potentially allowing problems in the construction field to be addressed. Although text mining techniques have been used in the construction field for many years, there is a lack of recent reviews focused on their development and application from a literature analysis perspective; therefore, we conducted a review with the aim of filling this gap. We use a combination of bibliometric and manual literature analyses to systematically review the text mining-based literature related to the construction field from 1997 to 2022. Specifically, publication analysis, collaboration analysis, co-citation analysis, and keyword analysis were conducted on 185 articles collected from the SCOPUS database. Based on a read-through of the 185 papers, the current research topics in text mining were manually determined and sorted, including tasks and methods, application areas, and core methods and algorithms. The presented results provide a comprehensive understanding of the current state of TM techniques, thereby contributing to the further development of TM techniques in the construction industry.

Keywords: construction industry; text mining; bibliometric analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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