Adoption of Farm Technologies across the Terai Region of West Bengal: A Comparative Topic Modelling Study of Empirical Literature Review - Saha, Debraj; Thakur, Soumyadeep; Das, Kalyan Kanti (International Journal of Bio-resource and Stress Management, 2026)
This study was executed from June, 2025 to January, 2026 in the Terai region of West Bengal mainly in Jalpaiguri and Cooch Behar district. The objectives were to identify technologies introduced in KVK villages over the past years, compare adoption gaps and performance between intervened and non-intervened farmers, analyse socio-technical and economic determinants, and design a feasible extension roadmap. To achieve these objectives, a systematic qualitative comparative analysis using literature review and advanced topic modelling was undertaken. A curated corpus of forty-five high-quality researches was constructed through rigorous inclusion criteria and quality assessment, followed by preprocessing and implementation of five computational approaches: Non-negative Matrix Factorization (NMF), Latent Dirichlet Allocation (LDA), Latent Semantic Analysis (LSA), and optimized variants. Multi-metric evaluation integrated reconstruction error, perplexity, topic diversity, interpretability, and computational efficiency. Results revealed consistent thematic clusters across models, including the central role of KVK as institutional hubs, gendered pathways of adoption through SHGs and training, and regional specificity, with Jalpaiguri and Cooch Behar emerging as technology adoption hotspots. Technology-specific themes such as solar irrigation under PM-KUSUM, mechanization via power tillers, direct-seeded rice, and integrated pest management appeared across findings. Divergence patterns highlighted methodological trade-offs like NMF with count data produced granular differentiation, while probabilistic LDA yielded more coherent narrative themes. The findings underscored both robust thematic structures and methodology-dependent artifacts, positioning topic modelling as a valuable but interpretive tool. This study provided a data-driven foundation for inclusive agricultural strategies tailored to smallholder realities in South Asia.