In this thesis, text mining was used to analyze the papers in Japanese Language Education Research published by the Korean Association for Japanese Language Education. Text mining was carried out using ‘KH Coder’ for 700 papers published from the ...
In this thesis, text mining was used to analyze the papers in Japanese Language Education Research published by the Korean Association for Japanese Language Education. Text mining was carried out using ‘KH Coder’ for 700 papers published from the first issue in 2001 to November 2022 (volume 61). The methods and results are described below.
[1] Using text mining techniques, we analyzed the frequency of occurrence of words in the data. The result of extracting the top 150 keywords used in the titles of the papers confirmed that many characteristic words related to Japanese language education appeared.
[2] In order to examine the connection and correlation between keywords, Co-occurrence Network was run to find out which words of the top 80 keywords were used in connection with each other. In addition, using the year of publication as an external variable, the study of the past 20 years was divided into three stages to confirm the trend and characteristic keywords of the study.
[3] As an example of case analysis of extracted words, the keywords of ‘online education’ such as [online], [non-face], and [e-learning] were analyzed to identify what kind of research has been conducted so far.
Through the above analysis, the significance of this study can be found in that it looked at the research results and trends published in the relevant academic journals, and identified the publication results and trends of papers related to Japanese language studies and education after 2000.