해양환경안전학회지 (Journal of the Korean Society of Marine Environment & Safety)

  • 제28권4호
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  • Pages.549-566
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  • 2022
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  • 1229-3431(pISSN)
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  • 2287-3341(eISSN)
해양환경안전학회 (The Korean Society of Marine Environment and safety)
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텍스트 마이닝을 활용한 해양수산부 법률 관련 연구동향 분석연구

Using Text Mining for the Analysis of Research Trends Related to Laws Under the Ministry of Oceans and Fisheries

  • Hwang, Kyu Won (Ocean Law and Policy Institute, Korea Institute of Ocean Science and Technology(KIOST)) ;
  • Lee, Moon Suk (Ocean Law and Policy Institute, Korea Institute of Ocean Science and Technology(KIOST)) ;
  • Yun, So Ra (Ocean Law and Policy Institute, Korea Institute of Ocean Science and Technology(KIOST))
  • 투고 : 2022.04.29
  • 심사 : 2022.06.27
  • 발행 : 2022.06.30
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⟨ 이전 논문 다음 논문 ⟩

초록

최근 인공지능(AI) 기술이 급격하게 발전되고 있으며, 이를 활용한 산업이 점차 확대되고 있다. 또한 사회과학 연구분야에서도 인공지능기술의 텍스트 마이닝을 활용한 분석연구가 활발하게 전개되고 있다. 해양수산부에서 소관하는 법률은 125여개로 해양환경, 수산, 선박, 어촌, 항만 등 다양한 분야에서 제정되었다. 해양수산부 법률을 대상으로 한 연구가 활발히 진행되고 있으며, 양적으로 꾸준하게 증가하고 있다. 이 연구는 해양수산부 법률 관련 연구논문을 대상으로 텍스트 마이닝을 적용하여 국내 연구동향을 분석하였다. 연구방법으로 첫째 텍스트 마이닝의 일종인 토픽 모델링을 수행하여 잠재된 토픽을 파악하였다. 둘째 특정 법률을 주제로 다룬 연구논문의 동시출현 네트워크 분석을 수행하여 주요 주제를 도출하였다. 마지막으로 저자 네트워크 분석을 수행하여 저자 간 사회 연결망을 탐색하였다. 분석결과 시기에 따라 핵심 토픽의 변화를 확인하였으며, 선박안전법, 해양환경관리법 등 법률별 주요 주제를 탐색하였다. 또한 저자 네트워크 분석하여 핵심 연구자를 도출하고, 저자 간 공동연구 성향을 파악하였다. 이를 통해 해양수산부 법률 관련 연구주제의 변화를 탐색하였으며, 향후 연구주제의 다양화와 해양수산 분야 연구의 양적 증가와 질적 성장을 기대한다.

Recently, artificial intelligence (AI) technology has progressed rapidly, and industries using this technology are significantly increasing. Further, analysis research using text mining, which is an application of artificial intelligence, is being actively developed in the field of social science research. About 125 laws, including joint laws, have been enacted under the Ministry of Oceans and Fisheries in various sectors including marine environment, fisheries, ships, fishing villages, ports, etc. Research on the laws under the Ministry of Oceans and Fisheries has been progressively conducted, and is steadily increasing quantitatively. In this study, the domestic research trends were analyzed through text mining, targeting the research papers related to laws of the Ministry of Oceans and Fisheries. As part of this research method, first, topic modeling which is a type of text mining was performed to identify potential topics. Second, co-occurrence network analysis was performed, focusing on the keywords in the research papers dealing with specific laws to derive the key themes covered. Finally, author network analysis was performed to explore social networks among authors. The results showed that key topics have been changed by period, and subjects were explored by targeting Ship Safety Law, Marine Environment Management Law, Fisheries Law, etc. Furthermore, in this study, core researchers were selected based on author network analysis, and the tendency for joint research performed by authors was identified. Through this study, changes in the topics for research related to the laws of the Ministry of Oceans and Fisheries were identified up to date, and it is expected that future research topics will be further diversified, and there will be growth of quantitative and qualitative research in the field of oceans and fisheries.

키워드

과제정보

이 연구는 2022년 한국해양과학기술원의 "해양공간 통합 관리 연구(PEA0043)" 사업의 지원을 받아 수행되었으며, 지원에 감사드립니다.

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