27 pages, Precision agriculture, which has existed for over four decades, ensures efficient use of agricultural resources for increased productivity and sustainability with the use of technology. Due to the lingering perception that the adoption of precision agriculture has been slow, this study examines public thoughts on the practice of precision agriculture by employing social media analytics. A machine learning-based social media analytics tool—trained to identify and classify posts using lexicons, emoticons, and emojis—was used to capture sentiments and emotions of social media users towards precision agriculture. The study also validated the drivers and challenges of precision agriculture by comparing extant literature with social media data. By mining online data from January 2010 to December 2019, this research captured over 40,000 posts discussing a myriad of concerns related to the practice. An analysis of these posts uncovered joy as the most predominant emotion, also reflected the prevalence of positive sentiments. Robust regulatory and institutional policies that promote both national and international agenda for PA adoption, and the potential of agricultural technology adoption to result in net-positive job creation were identified as the most prevalent drivers. On the other hand, the cost and complexity of currently available technologies, as well as the need for proper data security and privacy were the most common challenges present in social media dialogue.
