Fish and Paddy Culture: Fish Farmer’s Sentiment Analysis Using Machine Learning

Abstract

Fish and paddy culture is a type of integrated farming system in which fish are cultured in rice paddies, and the fish waste is used to fertilize the rice crops. Sentiment analysis can be used to understand the feelings and attitudes of fish farmers towards this farming system. To conduct sentiment analysis on fish farmers' opinions on fish and paddy culture, one would need to collect text data from various sources, such as social media posts, online forums, or surveys these text data consists of English, Hindi and Chhattisgarhi (Regional language of Chhattisgarh) text. The collected data would then be analysed using natural language processing (NLP) techniques to identify the sentiment expressed in each message. The results of the sentiment analysis will provide insights into the perceptions of fish farmers towards fish and paddy culture. For example, if the sentiment analysis reveals that fish farmers express positive sentiments towards fish and paddy culture, it could suggest that this farming system is well-received and popular among fish farmers. On the other hand, if the sentiment analysis reveals negative sentiments, it could indicate that fish farmers are facing challenges or difficulties with this farming system, and improvements may be needed. Overall, sentiment analysis can help fish farmers and policymakers gain a better understanding of the attitudes and opinions of fish farmers towards fish and paddy culture, and help identify areas for improvement or further research.