Sentiment Analysis using Machine Learning algorithms for Customer Product Reviews

The infrastructure of healthcare is undergoing development with Abstract—Customers and businesses engaged in online commerce are now engaged in global conversations through the medium of online reviews. When a potential purchaser is interested in making a purchase from an e-commerce behemoth such as Amazon, Flipkart, or one of the many others out there, they look at the ratings and feedback that previous buyers have given the goods. Potential purchasers find it tough to make educated selections about whether or not to acquire a product as a result of the vast amount of product reviews that are available online. Millions of evaluations are published every single day on various websites.It is necessary to categorise reviews according to whether the reviewer had a favourable or unfavourable attitude in order to derive useful information from a big number of reviews. It is possible to recover the text's subjective information by employing computer programmes and techniques such as sentiment analysis. In this project, we are making use of machine learning algorithms such as Support Vector Machines, Decision Trees, and Naive Bayes in order to recognise the sentiments expressed by our customers in their evaluations. The customer is helped in the process of making a purchasing decision by this sentiment study..