Identification and analysis of Indian farmers’ behavior toward adoption of new farming technologies and e-agriculture schemes through Twitter

Abstract This study examines the challenges and sentiments surrounding the adoption of new farming technologies and government schemes in India’s agriculture sector. Researchers gathered 491 reviews to identify key adoption challenges and analyzed 1,390 tweets to assess sentiments (positive, neutral, or negative) on these topics. Using count vectorizer, term frequency-inverse document frequency (TF-IDF), and FastText for feature extraction, TF-IDF with logistic regression achieved the highest accuracy at 0.91. The findings highlight major obstacles in the adoption of new farming technologies and schemes, analyze sentiment trends with six machine learning models and two deep learning models, and recommend enhanced communication, training, and awareness initiatives to boost adoption among farmers.