Computational analysis of the Pusa Samachar YouTube channel using audience engagement and sentiment analysis

Abstract Digital platforms have emerged as an important tool for agricultural communication by enabling faster, wider, and more interactive communication. A major advantage of these platforms is their ability to generate measurable interaction data for evaluating communication effectiveness. In this context, the present study performs a computational analysis of audience engagement, sentiment classification, and thematic communication patterns of the “Pusa Samachar” YouTube channel managed by the ICAR-Indian Agricultural Research Institute (IARI), New Delhi. A total of 705 uploaded videos and 7084 viewer comments were extracted. Video performance was assessed using engagement indicators, such as views, likes, and comments, sentiment analysis of comments was conducted using the VADER (Valence Aware Dictionary and Sentiment Reasoner) approach in Python. Thematic classification was done to identify dominant communication themes and audience concerns. The study found that the videos related to direct-seeded rice, crop disease management, crop varieties, and seed-related information generated higher audience engagement. In the theme-wise engagement analysis, extension & farmer outreach recorded the highest audience interaction, whereas crop management & agricultural practices exhibited the highest engagement rate (5.39%). The Kruskal-Wallis test showed significant differences across thematic categories in engagement rates ( p < 0.001). Concurrently, sentiment analysis showed the predominance of neutral comments (50.75%), followed by positive (44.30%) and negative (4.79%), suggesting that viewers primarily used the platform for information-seeking, feedback, and technical clarification. The study’s findings reflect the growing role of YouTube as an interactive digital agricultural platform, highlighting the importance of practical and farmer-oriented communication in strengthening the digital agricultural communication system.