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 weredismantled and there islack of measures for overseas advance and success. Therefore, this study aims to analyze the success factors of BTS by focusing onthe text mining techniques. After collecting Twitter's online postings using crawling technique, we will analyzein three text mining techniques: topic modeling, keyword extraction, andterm frequencyanalysis. By analyzing data with three text miningmethods, we willderivehow BTS couldsuccess globallyand 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 studiesorinterview, this study has implicationsin that the actual data was collected and analyzed through three text mining techniques.
Choi, Soobin; Park, Gayeon; and Kim, Hee-Woong, "A Text Mining Approach to the Analysis of BTS Fever" (2019). PACIS 2019 Proceedings. 37.