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Analysis of accident types at small and medium-sized construction sites based on web scraping and text mining

웹 스크래핑 및 텍스트마이닝에 기반한 중소규모 건설현장 사고유형 분석

  • Younggeun Yoon (Dept. of Occupational Safety & Housing Management, Cyber Hankuk University of Foreign Studies)
  • 윤영근 (사이버한국외국어대학교 산업안전.주택관리학부)
  • Received : 2023.10.20
  • Accepted : 2023.12.10
  • Published : 2024.01.31

Abstract

The construction industry's fatality count stands at 402, comprising approximately 46% of total industrial accidents. Notably, construction costs less than 5 billion won account for about 69%, so strengthening safety management at small and medium-sized construction sites is required. In this study, 19,511 accident investigation data were collected using web scraping. Through statistical analysis of the collected structured data and text mining analysis of the unstructured data, accident types and causes of accidents were analyzed by construction costs at sites less than 5 billion won. As a result, it was confirmed that there were differences in accident types and causes depending on the construction costs. It is hoped that the results of this study will be used for customized safety management at small and medium-sized construction sites.

건설업의 사고사망자 수는 402명으로 전체 산업의 약 46%이다. 이 중 50억원 미만의 건설현장이 약 69%를 차지하고 있어 중소규모 건설현장의 안전관리 강화가 요구된다. 본 연구에서는 웹 스크래핑을 이용하여 19,511건의 사고조사자료를 수집하였다. 수집된 정형 데이터에 대한 통계분석, 비정형 데이터에 대한 텍스트마이닝 분석을 통해 50억원 미만의 현장의 공사금액별 사고유형과 사고원인 분석을 진행하였다. 그 결과 공사금액별로 사고유형과 원인에 차이가 있음이 확인되었다. 본 연구의 결과가 중소규모 건설현장 맞춤형 안전관리에 활용되기를 기대한다.

Keywords

Acknowledgement

이 연구는 2023학년도 사이버한국외국어대학교 교내학술연구비의 지원에 의하여 이루어진 것임.

References

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