Machine Learning Techniques to Categorize the Sentiment Analysis of Amazon Customer Reviews

Natural language processing (NLP) oversees several critical activities, such as sentiment analysis (SA) and opinion mining (OM). It maintains track of the user's internal discourse about the product to determine their opinion. Many online retailers and sellers collect feedback from satisfied consumers to measure client happiness. Customers struggle to sort through the millions of reviews published daily to make an informed buying decision. Manufacturers are likewise having difficulty and spending significant time assessing this large amount of feedback. Presently, the issue of distinguishing between positive and negative reviews is examined. For this study, many Supervised Machine Learning algorithms, including support vector machine (SVM), Naïve Bayes, and Logistic Regression, were tested on Amazon's beauty items. Their precisions have been compared in this paper.