텍스트 마이닝 기법을 활용한 한국 문화정책 연구 경향 분석

The purpose of this study is to analyze the research trends of cultural policy research in Korea since 1989 through text mining techniques. Text mining techniques, which are actively used in the field of information engineering, are known with the techniques of classification, clustering, concept extraction, sentiment analysis, and document summarization through statistical pattern learning. The analysis target of this study were limited to 283 papers related to cultural policy including the multicultural policy published in 12 journals in the field of public administration from 1989 to 2016. According to the results of the analysis, the follow-up generations of Korean cultural policy research have not been revealed at least based on the academic journals that were the subjects of this study. In addition, it has been found that the study of subdivisions of cultural policy extracted from the analysis also tends to decrease. Of course, in terms of diversification of researchers and research themes, the trends can be interpreted positively. Nevertheless, it is also necessary to consider the fact that academic research has developed through accumulation and deepening processes and the accumulation should be the base of positive effects of diversification. Text mining techniques are known to increase the objectivity of contents analysis through the discovery of statistical patterns. Therefore, It is expected that those can be applied to the analysis of research trends in the field of broader range such as administration and policy for the future research. Also, it shows that there are various research areas for the practical development of effective policies. Due to one of the technical limitations of the paper, the contents of some papers could not be extracted as text data. Therefore, the results of this analysis should be interpreted more carefully.