A critical review of text-based research in construction: Data source, analysis method, and implications

Seungwon Baek, Wooyong Jung, Seung H. Han

Research output: Contribution to journalReview articlepeer-review

16 Citations (Scopus)


The advancement of natural language processing and text mining techniques facilitate automatic non-trivial pattern extraction and knowledge discovery from text data. However, text-based research has received less attention compared to image- and sensor-based research in the construction industry. Hence, this paper performs a comprehensive review to understand the current state and future insights of text analytics focusing on the data source and analysis method. This study identifies various kinds of text data sources from project documents as well as open data in the websites. In addition, the review finds that the ontology- and rule-based approach has been dominant, at the same time, recent research has attempted to apply the state-of-the-art machine learning methods. It is envisioned that there are potential advancements in construction engineering and management based on the latest text analysis methods along with the enriched data by the digital transformation.

Original languageEnglish
Article number103915
JournalAutomation in Construction
Publication statusPublished - 2021 Dec

Bibliographical note

Funding Information:
This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2020R1A2C1012739 ).

Publisher Copyright:
© 2021 Elsevier B.V.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction


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