빅데이터 텍스트 마이닝을 활용한 국내 중국어 교육 관련 학위 논문 동향 분석 ― 2000-2019년까지 20년간 연구 성과를 중심으로 (An Analysis on the Trend of Dissertation Results Related to Chinese Education in Korea Using Big Data Text Mining : A Study of 20 Years from 2000 to 2019)

서지정보

· 발행기관 : 중국어문학연구회
· 수록지 정보 : 중국어문학논집 / 119호 / 253 ~ 284페이지
· 저자명 : 최현미

초록

In this paper, I selected the research achievements of the dissertation papers related to Chinese language education and analyze the research trends of 20 years.
As such, we are going to utilize big data analysis methods to identify trends in research related to Chinese education in this paper. By utilizing big data analysis techniques, we want to understand the overall research trends of Chinese education-related dissertations published in Korea from 2000 to 2019.
To that end, the paper's title, publication date and abstracts of the dissertation, which were searched as keywords, were used as analysis data for the main paper. In particular, abstracts was divided into English and Korean literature records, so they were collected by dividing them into English data and Korean data.
And I used one of the big data analysis techniques, the text mining technique, to extract key word words and explore the interrelated relationship between words through the n-gram analysis method.
In order to analyze the overall research trends of the 20 years of the dissertation on Chinese education and to identify the trend of change in research trends along the time stream, this paper divided the 20 years into four quarters in total and carried out the extraction of key keyword words for each quarter. And through keyword analysis we will consider the characteristics of Chinese education research in each era.
Finally, based on the above results, I discussed the direction of future Chinese education research and how to develop.

영어초록

In this paper, I selected the research achievements of the dissertation papers related to Chinese language education and analyze the research trends of 20 years.
As such, we are going to utilize big data analysis methods to identify trends in research related to Chinese education in this paper. By utilizing big data analysis techniques, we want to understand the overall research trends of Chinese education-related dissertations published in Korea from 2000 to 2019.
To that end, the paper's title, publication date and abstracts of the dissertation, which were searched as keywords, were used as analysis data for the main paper. In particular, abstracts was divided into English and Korean literature records, so they were collected by dividing them into English data and Korean data.
And I used one of the big data analysis techniques, the text mining technique, to extract key word words and explore the interrelated relationship between words through the n-gram analysis method.
In order to analyze the overall research trends of the 20 years of the dissertation on Chinese education and to identify the trend of change in research trends along the time stream, this paper divided the 20 years into four quarters in total and carried out the extraction of key keyword words for each quarter. And through keyword analysis we will consider the characteristics of Chinese education research in each era.
Finally, based on the above results, I discussed the direction of future Chinese education research and how to develop.

참고자료

· 없음