ARTIFICIAL INTELLIGENCE–BASED ANALYSIS OF DISCOURSES ON SUSTAINABLE AGRICULTURE
SÜRDÜRÜLEBILIR TARIM SÖYLEMLERININ YAPAY ZEKA TABANLI ANALIZI
DOI : https://doi.org/10.35633/inmateh-79-56
Authors
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.
Abstract in Turkish



