Ocean and Polar Research

Korea Institute of Ocean Science & Technology (한국해양과학기술원)
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Frequency Analysis of Scientific Texts on the Hypoxia Using Bibliographic Data

논문 서지정보를 이용한 빈산소수괴 연구 분야의 연구용어 빈도분석

  • Lee, GiSeop (Ocean Data Science Section, KIOST) ;
  • Lee, JiYoung (Marine Environment Research Division, National Institute of Fisheries Science) ;
  • Cho, HongYeon (Ocean Data Science Section, KIOST)
  • 이기섭 (한국해양과학기술원 해양과학데이터운영실) ;
  • 이지영 (국립수산과학원 어장환경과) ;
  • 조홍연 (한국해양과학기술원 해양과학데이터운영실)
  • Received : 2019.03.18
  • Accepted : 2019.06.20
  • Published : 2019.06.30
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Abstract

The frequency analysis of scientific terms using bibliographic information is a simple concept, but as relevant data become more widespread, manual analysis of all data is practically impossible or only possible to a very limited extent. In addition, as the scale of oceanographic research has expanded to become much more comprehensive and widespread, the allocation of research resources on various topics has become an important issue. In this study, the frequency analysis of scientific terms was performed using text mining. The data used in the analysis is a general-purpose scholarship database, totaling 2,878 articles. Hypoxia, which is an important issue in the marine environment, was selected as a research field and the frequencies of related words were analyzed. The most frequently used words were 'Organic matter', 'Bottom water', and 'Dead zone' and specific areas showed high frequency. The results of this research can be used as a basis for the allocation of research resources to the frequency of use of related terms in specific fields when planning a large research project represented by single word.

Keywords

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Fig. 1. Comparisons of visualized top 100 Bigrams according to the citation weights (a, b); Variations of Bigram distribution (c) and rank (d)

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Fig. 2. Bigram frequency including ‘bay’ in Hypoxia articles: non citation weighted

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Fig. 3. Bigram frequency including ‘bay’ in Hypoxia articles: non citation weighted

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Fig. 4. Bigram frequency including ‘bay’ in Hypoxia articles: citation weighted

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Fig. 5. Co-occuring words network during 2001−2010

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Fig. 6. Co-occuring words network during last decade (2001−2010)

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Fig. 7. Distributions of raw and normalized citation (a, b) and annual variations of total citation (c)

Table 1. Ten Most Frequent words ranked by Inverse Document Frequency (IDF)

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