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Discovering the Research Topics on Construction Safety and Health Using Semi-Supervised Topic Modeling

Authors :
Kai Zhou
Jun Wang
Baabak Ashuri
Jianli Chen
Source :
Buildings, Vol 13, Iss 5, p 1169 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Safety and health have been one of the major issues in the construction industry worldwide for decades, and the relevant research has correspondingly drawn much attention in the academic field. Considering the expanding size and increasing heterogeneity of this research field, this paper proposes the topic modeling approach to cluster latent topics, extract coherent keywords, and discover evolving trends over the past three decades. Focusing on a total of 1984 articles published in 27 different journal sources until February 2023, this paper applied both unsupervised topic modeling techniques—Latent Dirichlet Allocation (LDA) and Correlation Explanation (CorEx)—and their semi-supervised versions—Guided LDA and Anchored CorEx. The evolving trends and inter-relationship of 15 research topics generated by the Anchored CorEx model (the best-performing model) were analyzed. Top-listed documents of major topics were analyzed to discuss their standalone research focuses. The results of this paper provided helpful insights and implications of existing research and offered potential guides for future research on construction safety and health by helping researchers (1) select research topics of interest and clearing decaying topics; (2) extract the top words of each research topic using systematic approaches; and (3) explore the interconnection of different research topics as well as their standalone focuses.

Details

Language :
English
ISSN :
20755309
Volume :
13
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Buildings
Publication Type :
Academic Journal
Accession number :
edsdoj.3cf4147a73a349b4b29e666f5cea6983
Document Type :
article
Full Text :
https://doi.org/10.3390/buildings13051169