Keyword Network Analysis of Research Trends in Makeup

Purpose: This study aims to identify research on makeup-related topics from the past decade using keyword network analysis.Methods: This study used keyword network analysis to extract data from the Korea Citation Index journal database of the National Research Foundation of Korea. A total of 585 papers related to makeup, published between 2013 and 2022, were used for the analysis.Results: An examination of the frequency of makeup-related keywords indicated that “image” displayed the highest frequency, followed by “art makeup,” “design,” “cosmetics,” “color,” and “semi-permanent makeup.” The study then classified the year of publication into the first (2013–2017) and second (2018–2022) periods. The terms “image,” “color,” “design,” and “art makeup” and “cosmetics,” “image,” “art makeup,” “design,” and “semi-permanent makeup” were studied in these orders during the first and second periods, respectively. Third, the study explored the properties of keywords using centrality analysis. The results indicated that the keyword with the most interaction with other keywords is “image,” whereas “design” and “art makeup” are keywords with a high centrality of connection with other keywords used in makeup-related research. Thus, the result implies that this topic is important.Conclusion: Research related to makeup is being conducted on various topics, including image, cosmetics, color, art, behavior, service, and education. However, convergence research, such as the Fourth Industrial Revolution and artificial intelligence (AI), is being conducted, and keywords related to this are expected to appear in several cases in the future.