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A text mining-based thematic model for analyzing construction and demolition waste management studies

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Abstract

Over the years, numerous studies have been conducted to investigate construction and demolition waste (CDW) management problems. However, the massive amount of literature brings challenges to scholars because it is difficult and time-consuming to manually identify research emphasis from the literature. Therefore, a method that can informationize literature collection and automatically detect insights from the identified literature is worthy of exploration. This paper attempts to present a comprehensive thematic model by combining Latent Dirichlet Allocation, word2vec, and community detection algorithm on python to detect insights from CDW management literature. Based on the database of Web of Science, 641 articles published between 2000 and 2019 are retrieved and used as the sample for analysis. The comprehensive thematic results reveal a four-domain knowledge map in CDW management research, which covers (1) introducing current situation of CDW management, (2) quantifying CDW generation, (3) assessing CDW and by-products, and (4) facilitating waste diversion. Future research directions in CDW management research have also been discussed. The results prove that the comprehensive thematic model is useful in mining insights from CDW management literature.

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Funding

This research was conducted with the support of the National Nature Science Foundation of China (Grant No.71974132), the Natural Science Foundation of Guangdong Province, China (Grant No. 2018A0303130037; 2019A1515011794), and Shenzhen Government Nature Science Foundation (Grant No. JCYJ20190808115809385).

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Authors and Affiliations

  1. Department of Construction Management and Real Estate, College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, People’s Republic of China

    Zhikun Ding & Rongsheng Liu

  2. School of Management, Guangzhou University, Guangdong, 510006, People’s Republic of China

    Hongping Yuan

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  1. Zhikun Ding
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  2. Rongsheng Liu
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  3. Hongping Yuan
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Contributions

DZ: idea, conceptualization, supervision. LR: writing-original draft preparation, editing, methodology, visualization. YH: writing-reviewing, editing, supervision.

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Correspondence to Hongping Yuan.

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Appendices

Appendix A: LDA topic models of CDW management

Table 10 LDA analysis result in phase 1
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Table 11 LDA analysis result in phase 2
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Table 12 LDA analysis result in phase 3
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Appendix B: Thematic analysis of CDW management

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Thematic network model in phase 1

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Fig. 17
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Thematic network model in phase 2

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Fig. 18
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Thematic network model in phase 3

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Ding, Z., Liu, R. & Yuan, H. A text mining-based thematic model for analyzing construction and demolition waste management studies. Environ Sci Pollut Res 28, 30499–30527 (2021). https://doi.org/10.1007/s11356-021-13989-1

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