Trend Analysis on Hair and Scalp Research Utilizing Text Mining

Abstract

This study analyzes the research trends related to "hair" and "scalp" by examining scholarly articles. To compare the differences in research topics across various fields and analyze the correlation between keywords, the statistical software R Studio was employed. The aim was to understand the types of keywords extracted through data analysis, visually grasp the trends in research, and propose future development directions and solutions. The results showed a steady increase in the number of published papers, with an 8.90% increase in the first phase, 22.0% in the second, 31.7% in the third, and 37.3% in the fourth. Additionally, the research was distributed across various fields without bias towards a specific topic, as evidenced by the word cloud analysis. The analysis of keyword rankings by phase revealed that the first phase focused on hair design, the second on fieldwork and education, the third on the beauty industry, and the fourth on beauty education. The topic-based word distribution graph formed six groups, specifically related to beauty: 'hair growth', 'satisfaction', 'hair design', 'status survey', 'beauty education', and 'experiment/measurement'. The percentage of papers by topic showed 'hair growth' leading with 24.7%, followed by 'satisfaction' at 22.5%, 'hair design' at 19.4%, 'status survey' at 16.0%, 'beauty education' at 13.6%, and 'experiment/measurement' at 3.8%. The ratio of topics over time indicated that early on, research was actively conducted on hair design related to fieldwork, but as time progressed, studies on satisfaction surveys and beauty education became more prevalent. In conclusion, from 2001 to 2022, research related to "hair" and "scalp" has been actively conducted across various fields, indicating that the beauty industry, which previously remained at a technical level, has developed into a higher level of technology through academic advancement, laying the foundation to meet consumers' needs.