Prediction of K-Beauty Industry Trend Using Big Data

Abstract

Recently, global brands have cited K-beauty as the main keyword that inspires product innovation, and K-beauty is also mentioned as a trendy keyword in famous beauty stores, such as preparing a K-beauty section. This study conducted unstructured big data analysis to confirm trends of K-beauty. To this end, keywords related to K-beauty were collected through online communication such as Naver, Daum, and Google using the social network analysis program called Textom. The collection period was set from Jan 2020 to AUG 2022, and a total of 24.683 keywords were collected, and a total of 60 keywords were used for the study by refining unnecessary keywords. The results are as follows. First, performing frequency, TF-IDF analysis, important keywords such as cosmetic products, beauty expo, premium market, and beauty industry were presented. Next, semantic network analysis showed that degree centrality was cosmetic products, beauty expo, and premium market, closeness centrality was award, yakson house, and beauty promotion. betweeness centrality was Korean culture experience, overseas buyer, and trends. Finally, CONCOR analysis resulted in a cluster of six groups: Cosmetics manufacturer, beauty products, beauty exporter, the Korean wave & distribution, beauty growth, beauty business. These analysis results confirm trends related to K-beauty, key components and sales channels for K-beauty industry. In addition, it is judged that it will propose meaningful implications for establishing effective data presentation and marketing strategies for research related to demand for K-beauty.