A Study on the Make-up Trends using Unstructured Big Data: Focusing on Make-up Keyword Changes in the Last 10 Years

Abstract

This study utilized Textom, optimized for big data analysis using unstructured data, to examine the changes in makeup trends over the past decade. It collected various texts from news, blogs, and cafe media on portal sites, spanning a total of ten years from January 2013 to December 2022. The research was conducted in five stages, each covering two years, to observe keyword trends. The results showed that makeup trends have continuously evolved through the integration and interaction with various fields such as digital technology, the beauty industry, art, and healthcare. Digital technology has created new forms and methods of makeup, and makeup has contributed to the utilization and development of digital technology. Additionally, the interaction between digital technology and makeup has enhanced their respective values and influenced consumers' makeup-related behaviors and preferences. This study analyzed the changes and developments in makeup trends over the last decade using unstructured big data, examining various factors and relationships related to makeup trends to predict future trends. This has academic and practical significance in product development and marketing in the beauty industry, consumers' access to makeup information and purchasing behavior, and makeup education and culture. However, such data can suffer from sample bias or lack representativeness, and there can be difficulties in accurately measuring makeup trend information. Therefore, future research should select a variety of platforms or channels, and analyze differences and changes in makeup trends according to users' demographic characteristics. Additionally, it is necessary to collect and analyze structured data on makeup trends to integrate with or complement unstructured data.