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

محفوظ في:
التفاصيل البيبلوغرافية
الحاوية / القاعدة:Buildings vol. 15, no. 16 (2025), p. 2817-2839
المؤلف الرئيسي: Lee, Kiseok
مؤلفون آخرون: Song Taegeun, Shin Yoonseok, Yoo Wi Sung
منشور في:
MDPI AG
الموضوعات:
الوصول للمادة أونلاين:Citation/Abstract
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024 7 |a 10.3390/buildings15162817  |2 doi 
035 |a 3243994044 
045 2 |b d20250101  |b d20251231 
084 |a 231437  |2 nlm 
100 1 |a Lee, Kiseok  |u Overseas Investment Development POG, SHIN and KIM LCC, Seoul 03155, Republic of Korea; ks8952@nate.com 
245 1 |a Developing a Sentiment Lexicon-Based Quality Performance Evaluation Model on Construction Projects in Korea 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a 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. 
653 |a Performance evaluation 
653 |a Inspection 
653 |a Documentation 
653 |a Structural equation modeling 
653 |a Language 
653 |a Correlation analysis 
653 |a Failure rates 
653 |a Quality control 
653 |a Data mining 
653 |a Project engineering 
653 |a Business metrics 
653 |a Structural failure 
653 |a Construction industry 
653 |a Quality assessment 
653 |a Quality standards 
653 |a Construction sites 
653 |a Quality management 
653 |a Supervision 
653 |a Conformity 
653 |a Information processing 
653 |a Unstructured data 
653 |a Performance management 
700 1 |a Song Taegeun  |u New Growth Procurement Research Center, Korea Institute of Procurement, Seoul 06226, Republic of Korea; song8444@kip.re.kr 
700 1 |a Shin Yoonseok  |u Department of Architectural Engineering, Kyonggi University, Kyonggi-do 16227, Republic of Korea; shinys@kyonggi.ac.kr 
700 1 |a Yoo Wi Sung  |u Department of Construction Economics & Finance Research, Construction & Economy Research Institute of Korea, Seoul 06050, Republic of Korea 
773 0 |t Buildings  |g vol. 15, no. 16 (2025), p. 2817-2839 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3243994044/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3243994044/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3243994044/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch