Artificial Intelligence–Based Analysis of Discourses on Sustainable Agriculture
INMATEH - AGRICULTURAL ENGINEERING, cilt.79, sa.2, ss.716-731, 2026 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 79 Sayı: 2
- Basım Tarihi: 2026
- Doi Numarası: 10.35633/inmateh-79-56
- Dergi Adı: INMATEH - AGRICULTURAL ENGINEERING
- Derginin Tarandığı İndeksler: Academic Search Ultimate (EBSCO), Scopus, Emerging Sources Citation Index (ESCI), Compendex, CAB Abstracts
- Sayfa Sayıları: ss.716-731
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Akdeniz Üniversitesi Adresli: Evet
Özet
This study examines how sustainable agriculture is represented in the digital public sphere, focusing on technology-driven agricultural systems. A dataset of 13,354 English posts from the X platform (January 2026) was collected, with 10,782 analysed after preprocessing. The methodology integrates text mining, TF-IDF keyword extraction, BERT-based sentiment analysis, and LDA topic modelling. Results show predominantly neutral discourse (65.27%), reflecting informational content, while positive discourse (33.17%) highlights smart farming and innovation. Negative content (1.56%) addresses structural challenges. Three themes emerge: climate-oriented sustainability, community-based practices, and technology-driven agriculture, emphasizing the role of digital technologies in shaping sustainable agricultural systems.