Abstract
This study analyzed keywords on skin collected by social network such as Naver’ & Daum’s Jisik-in, cafes, blogs, etc. from Jan. 2017 to 2019 Dec by applying big data analysis. The results were as follows. First, from the analysis of text mining, the keywords that appeared most in 2017, 2018 and 2019 were acne. Second, TF-IDF did not differ significantly by year. The skin was the most important keyword. Third, as a result of N-gram analysis, it was found that in 2017 or 2018, ‘skincare shop’-‘characteristics’ and in 2019, ‘proper skin care’-‘doing’ was found. Fourth, as a result of semantic network analysis, men’s skincare, special occasions’ skincare, acne & pore, hypoallergic skincare were the main factors in 2017. In 2018, acne, prickle & dryness, atopy, pore, elasticity, sebum, anti-aging and sebum, and in 2019, home care, customized care, anti-aging and atopy were the main keywords. From the results, the biggest concerns that Koreans have been acne, atopy, dryness, pores, and sebum.
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