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.

This research used a questionnaire survey to examine the positive and negative opinions of Japanese university students about living with robots. The results show that the effect of educational background on the hope of living with a robot is statistically significant, that gender affects negative attitudes toward the social influence of robots, and that negative correlation between the hope of living with a robot and negative attitudes toward emotional interaction with robots is statistically significant. An exploratory qualitative classification reveals that most Japanese undergraduates hold the negative opinion that they have no need to live with robots because they are not alone.