Analysis of Research Trends in Cosmetology Education using Text Mining

Abstract

Identifying academic research trends is an essential task to understand the development patterns of how the discipline has changed in the times and social trends based on the accumulated research results so far, and further establish academic identity. This study was conducted according to the following procedure to analyze the trend of Cosmetology Education Research using text mining. The research procedure proceeded to the stages of data collection, data cleaning, text mining, network analysis, and CONCOR analysis. This study conducted a trend analysis of Cosmetology Education Research using text mining, one of the big data analysis methods, to suggest that the beauty field also needs to respond to changes in the times. Through this, it was confirmed that research on the curriculum and learning satisfaction is most actively conducted, and there is a research variations in the school system and the major. However, as this study has been limited to the field of cosmetology education, it is believed that it can be meaningful as more valuable basic data if big data analysis is conducted by expanding the scope of research.