A text mining approach to the analysis of BTS fever

K-POP is steadily growing with global competitiveness. The rise of K-POP's popularity has continued to create Korean idol groups. However, many idol groups were dismantled and there is lack of measures for overseas advance and success. Therefore, this study aims to analyze the success factors of BTS by focusing on the text mining techniques. After collecting Twitter's online postings using crawling technique, we will analyze in three text mining techniques: topic modeling, keyword extraction, and term frequency analysis. By analyzing data with three text mining methods, we will derive how BTS could success globally and form a huge fandom. And with the derived key factors, we will suggest a success strategy based on the analysis results. In contrast to previous studies that were centered on case studies or interview, this study has implications in that the actual data was collected and analyzed through three text mining techniques.