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Developing a Sentiment Lexicon-Based Quality Performance Evaluation Model on Construction Projects in Korea

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Publicat a:Buildings vol. 15, no. 16 (2025), p. 2817-2839
Autor principal: Lee, Kiseok
Altres autors: Song Taegeun, Shin Yoonseok, Yoo Wi Sung
Publicat:
MDPI AG
Matèries:
Performance evaluation
Inspection
Documentation
Structural equation modeling
Language
Correlation analysis
Failure rates
Quality control
Data mining
Project engineering
Business metrics
Structural failure
Construction industry
Quality assessment
Quality standards
Construction sites
Quality management
Supervision
Conformity
Information processing
Unstructured data
Performance management
Accés en línia:Citation/Abstract
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Resum:The increasing frequency of structural failures on construction sites emphasizes the critical role of rigorous supervision in ensuring the quality of both construction processes and materials. Current regulatory frameworks mandate the production of detailed supervision reports to provide comprehensive evaluations of construction quality, material compliance, and site records. This study proposes a novel approach to harnessing unstructured reports for automated quality assessment. Employing text mining techniques, a sentiment lexicon specifically tailored for quality performance evaluation was developed. A corpus-based manual classification was conducted on 291 relevant words and 432 sentences extracted from the supervision reports, assigning sentiment labels of negative, neutral, and positive. This sentiment lexicon was then utilized as fundamental information for the Quality Performance Evaluation Model (QPEM). To validate the efficacy of the QPEM, it was applied to supervision reports from 30 construction sites adhering to legal standards. Furthermore, a Pearson correlation analysis was performed with the actual outcomes based on the legal requirements, including quality test failure rate, material inspection failure rate, and inspection management performance. By leveraging the wealth of unstructured data continuously generated throughout a project’s lifecycle, this model can enhance the timeliness of inspection and management processes, ultimately contributing to improved construction performance.
ISSN:2075-5309
DOI:10.3390/buildings15162817
Font:Engineering Database