Akademik Veri Yönetim Sistemi
Food and Humanity, cilt.7, 2026 (ESCI, Scopus)
This study provides a comprehensive bibliometric analysis of research on artificial intelligence (AI) applications in eating behaviour and food choice between 2000 and 2025. Data were retrieved from the Web of Science Core Collection and analysed using Biblioshiny (Bibliometrix R package) and VOSviewer to examine publication trends, citation patterns, collaboration networks, and keyword co-occurrence. The results reveal a marked acceleration in AI-related nutrition research from 2020 onwards, with publication output increasing substantially during the 2023–2025 period, noting that 2025 represents a partial publication year, largely driven by advances in machine learning, deep learning, and image recognition techniques for dietary assessment and behavioural prediction. Thematic evolution analysis indicates a shift from an early focus on calorie tracking and food recognition toward more complex topics such as personalised nutrition, emotional eating, and ethical considerations in AI-driven interventions. Overall, the findings demonstrate that AI is increasingly shaping eating behaviour and food choice research by enabling advanced analytical approaches and personalised solutions. Nevertheless, important challenges related to ethical data use, cultural generalisability, and interdisciplinary integration remain. This bibliometric overview provides an evidence-based framework to inform future research directions and support the responsible integration of AI into eating behaviour and food choice research.