Can YouTube serve as a source of information for precision farming? A text mining approach for YouTube videos

Purpose The main goal of this study is to determine whether YouTube offers information on precision farming, identify which locations received the most video uploads and analyse what each channel specialises in. Design/methodology/approach This study collected data using Webometric Analyst software, performed sentiment analysis with Python and conducted text analysis in MS Excel. It examined 394 videos and 6,861 comments. Findings The results indicate that most films are valuable, primarily because agricultural professionals uploaded them. It has also been found that the majority of videos focus on agricultural instruments and technology, while uploaders demonstrate the use of various technologies and tools in precision farming. The second-largest group of videos features case studies or testimonials, indicating that specific, established precision agricultural methods are emphasised. Research limitations/implications This study has possible limitations because YouTube shorts were omitted from the data sets, which may affect the interest of viewers and developers. Originality/value The data collected and utilised in this study are correct and original in nature.