Trend Analysis of Skincare Products for Pregnant Women Using Textmining

• 발행기관: 한국응용과학기술학회 (구.한국유화학회)
• 저자명: 박형범(Hyung-Bum Park) 박정연(Jeong-Yeon Park)
• 간행물 정보: 『한국응용과학기술학회지』제42권 제1호, 58~66쪽, 전체 9쪽
• 주제분류: 공학 > 화학공학
• 파일형태: PDF
• 발행일자: 2025.02.28

국문 초록

This study explores trends in skincare products for pregnant women using text mining to analyze consumer preferences for safety and functionality. Data were collected from Naver blogs, cafes, and Facebook between September 2023 and August 2024 and processed using the Textom platform. Through text mining and semantic network analysis, 50 significant keywords were selected, and centrality measurements such as degree and eigenvector centrality were applied to assess keyword importance. CONCOR analysis categorized these keywords into structural equivalence groups, revealing key consumer priorities, including ingredient safety, moisturizing properties, and product recommendations. The findings highlight the growing demand for dual-purpose skincare products suitable for both pregnant women and infants, as well as the increasing influence of consumer reviews in product selection. Academically, this research underscores the effectiveness of text mining in understanding niche consumer markets. However, the study's reliance on specific online platforms presents a limitation, as it may not fully represent broader consumer preferences. Future research should incorporate diverse data sources and quantitative analyses to further validate product efficacy and consumer satisfaction.

목차

1. Introduction

2. Research method

3. Results and discussion

4. Conclusion

References

키워드

Pregnancy skincare Text mining Semantic network analysis CONCOR Consumer preferences