Analysis of Beauty Device Research Trends Using Unstructured Big Data : 2004 2023 Focusing on the Amount of Keyword Change in Academic Journals

This study investigated the recent trend of device research in the beauty market through unstructured big data analysis based on keywords in beauty device-related articles published in Korean academic journals from 2004 to 2023. The data were collected from articles published in Naver, Google News, blogs, cafes, and DBpia. Keyword extraction and refinement, frequency and co-occurrence keyword analysis, semantic linkage network analysis, and QAP correlation analysis were conducted using the Textom program. The results of the study revealed developments in beauty device-related research by analyzing keyword frequency, connection centrality, and dominance centrality by era. In particular, a significant increase in research interest in mask use and home beauty devices were found since 2019. Based on these findings, academic implications were drawn, including changes in research trends over time, the need for a multidisciplinary approach, diversification of research topics and directions, and advancements in research methodologies; practical implications were presented, including setting directions for product development and innovation, improving marketing strategies, monitoring market trends, and strengthening consumer education and communication strategies. This study is expected to provide useful insights for the research and development of marketing strategies in the beauty device market.