Sentiment Analysis for Product Review using Machine Learning and NLP

This abstract outlines a machine learning (ML) approach for performing sentiment analysis on product reviews using Natural Language Processing (NLP). The methodology involves utilizing NLP techniques to preprocess textual data and applying ML models, such as Naive Bayes and Support Vector Machines, to classify review sentiment into categories like positive, negative, or neutral. This automation provides businesses with scalable tools to efficiently analyze extensive customer feedback, gauge overall satisfaction, identify specific product strengths and weaknesses, and inform data-driven decisions for future product enhancements and marketing strategies.