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Analysis of Research Trends Using Text Mining

텍스트 마이닝을 활용한 연구 동향 분석

  • 심재권 (고려대학교 영재교육원)
  • Received : 2020.02.29
  • Accepted : 2020.04.28
  • Published : 2020.04.30

Abstract

This study used the text mining method to analyze the research trend of the Journal of Creative Information Culture(JCIC) which is the journal of convergence. The existing research trend analysis method has a limitation in that the researcher's personality is reflected using the traditional content analysis method. In order to complement the limitations of existing research trend analysis, this study used topic modeling. The English abstract of the paper was analyzed from 2015 to 2019 of the JCIC. As a result, the word that appeared most in the JCIC was "education," and eight research topics were drawn. The derived subjects were analyzed by educational subject, educational evaluation, learner's competence, software education and maker culture, information education and computer education, future education, creativity, teaching and learning methods. This study is meaningful in that it analyzes the research trend of the JCIC using text mining.

본 논문은 융복합 논문지인 창의정보문화연구의 연구 동향을 분석하기 위한 목적으로 텍스트 마이닝 방법을 활용하였다. 기존의 연구동향 분석방법은 전통적인 내용분석 방법을 사용하여 연구자 개인의 성향이 반영되는 한계가 있었다. 따라서, 기존 연구 동향 분석의 한계를 보완하고자 본 논문에서는 토픽 모델링 기법을 사용하였고, 창의정보문화연구 논문지의 2015년에서 2019년까지 발간된 논문 전체의 영문초록을 분석하였다. 분석 결과, 가장 많이 등장한 단어는 "education"이었고, 8개의 연구 주제가 도출되었다. 도출된 주제는 교육대상, 교육평가, 학습자역량, 소프트웨어와 메이커 문화, 정보교육과 컴퓨터교육, 미래교육, 창의성, 교수학습방법으로 분석되었다. 본 논문의 텍스트 마이닝을 활용하여 융복합연구 논문지의 연구동향을 분석하였다는 점에서 의의가 있다고 할 수 있다.

Keywords

References

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