Artificial Intelligence–Based Analysis of Discourses on Sustainable Agriculture
INMATEH - AGRICULTURAL ENGINEERING, vol.79, no.2, pp.716-731, 2026 (ESCI, Scopus)
- Publication Type: Article / Article
- Volume: 79 Issue: 2
- Publication Date: 2026
- Doi Number: 10.35633/inmateh-79-56
- Journal Name: INMATEH - AGRICULTURAL ENGINEERING
- Journal Indexes: Academic Search Ultimate (EBSCO), Scopus, Emerging Sources Citation Index (ESCI), Compendex, CAB Abstracts
- Page Numbers: pp.716-731
- Open Archive Collection: AVESIS Open Access Collection
- Akdeniz University Affiliated: Yes
Abstract
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.