텍스트 마이닝을 활용한 중국인 학습자 대상 한국어교육 연구 동향

Analysis of Korean Language Education Research Trends for Chinese Korean Language Learners on text mining -Based on Co-occurrence & Social network analysis

The purpose of this thesis is to find out the variation trends that aim for the objects, Chinese Korean language learners. It uses research-tendency analysis in Korean-language education, among the Korean academic community. The research object is a collection of academic papers’ titles published in Korea within a certain annual range. The method of this research is based on the text mining analysis whose objects are academic papers’ titles of keywords. Afterward, it analyzes the co-occurance words. Moreover, through the social network map, it finds out the research development trends. Research trend analysis is extensively used in the study of Korean language education. However, this kind of thesis, which uses research trend analysis for the specific objects, Chinese Korean language learners, has rarely been published. This study is based on statistical analysis. In addition, it analyzes the relationship between the number of papers and the number of Chinese students. Furthermore, the study uses R as a statistical tool for the analysis of the co-occurance words. It imports the results into Pajek and then makes into a social network map. This thesis uses text mining to analyze the trends of the research topics. Consequently, it finds out the differences in the research trends of academic papers in three different stages in the field of Korean language education for Chinese Korean language learners.