미래기술융합논문지 (Journal of Advanced Technology Convergence)

한국융합학회 (Korea Convergence Society)
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텍스트 마이닝을 활용한 재생에너지 연구 동향: SCOPUS DB 논문을 중심으로

A Study on Renewable Energy Research Trends Using Text Mining: Focusing on SCOPUS DB Papers

  • 박성택 ((재)천안과학산업진흥원)
  • 투고 : 2023.07.25
  • 심사 : 2023.09.21
  • 발행 : 2023.09.30
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초록

전세계적으로 기후 변화 문제가 심화되고 있으며, 화석연료의 사용 증가로 인한 다양한 문제들이 야기되고 있다. 특히 탄소중립 정책이 가속화됨으로 재생에너지에 대한 관심이 증가하고 있는 추세이다. 이에 본 연구에서는 SCOPUS DB를 활용하여 신재생에너지 연구 동향을 파악하였다. 초록 제공이 가능한 1,353개의 데이터를 확보하고 이를 분석할 수 잇도록 데이터 전처리를 수행하고 분석을 수행하였다. 토픽모델링 분석 결과 중요한 키워드로 renewable와 enegy로 나타났다. 이 외에도 electricity, solar, wind, 등이 중요한 키워드로 분석이 되었다. 본 연구 결과를 통해 신재생에너지 관련 기업의 실무자들이 신재생에너지 관련 연구동향을 실무에 활용할 수 있을 것으로 기대한다.

The problem of climate change is intensifying around the world, and the increasing use of fossil fuels is causing a variety of problems. In particular, interest in renewable energy is increasing due to the acceleration of carbon neutrality policies. In this study, we utilized SCOPUS DB to identify trends in renewable energy research. We obtained 1,353 data for which abstracts were available and performed data preprocessing to analyze them. Topic modeling analysis showed that renewable and energy were the most important keywords. In addition, electricity, solar, wind, etc. were analyzed as important keywords. Through the results of this study, it is expected that practitioners of renewable energy-related companies can utilize the research trends related to renewable energy in practice.

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참고문헌

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