Journal of the Korean Society for Aviation and Aeronautics (한국항공운항학회지)

The Korean Society for Aviation and Aeronautics (한국항공운항학회)
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Analysis of Aviation Safety Management Issues using Text Mining

Text Mining 기법을 활용한 항공안전관리 이슈 분석

  • 권문진 (한국항공대학교 항공운항관리학과) ;
  • 이장룡 (한국항공대학교 항공운항학과)
  • Received : 2023.10.16
  • Accepted : 2023.10.26
  • Published : 2023.12.31
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Abstract

In this study, a total of 2,584 domestic research papers with the keywords "Aviation Safety" and "Aviation Accidents" were subjected to Text Mining analysis. Various text mining techniques, including keyword frequency analysis, word correlation analysis, network analysis, and topic modeling, were applied to examine the research trends in the field of aviation safety. The results revealed a significant increase in research using the keyword "Aviation Safety" since 2015, with over 300 papers published annually. Through keyword frequency analysis, it was observed that "Aircraft" was the most frequently mentioned term, followed by "Drones" and "Unmanned Aircraft." Phi coefficients were calculated for words closely related to "Aircraft," "Aviation," "Drones," and "Safety." Furthermore, topic modeling was employed to identify 12 distinct topics in the field of aviation safety and aviation accidents, allowing for an in-depth exploration of research trends.

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Acknowledgement

본 논문은 2023년도 한국항공운항학회 춘계학술대회 발표논문을 발전·적용하였습니다.

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