Analysis of 50 Years of Health Food Research Trends Using Natural Language Processing and Generative AI
Yoshiyuki Kobayashi, Takumi Uchida, Takahiro Inoue, Yusuke Iwasaki, Rie Ito, Koichi Saito, Hiroshi Akiyama, Kazuhiko Tsuda, Kenichi Yoshida · Procedia Computer Science · 2024
This study investigates trends in health food research from 1975 to 2024 using text mining and generative AI. Analyzing 92,028 journal entries from Scopus revealed a significant increase in publications, with key topics including nutrients, bioactive compounds, disease prevention, and research methods. AI-assisted classification yielded 12 categories reflecting the field’s multidisciplinary nature. Trends include a growing focus on nutrients, health conditions, study design, and food production and consumption context. The findings highlight the increasingly interdisciplinary landscape of health food research, informing future directions and evidence-based decision-making.