With the advent of technology in recent years, people depend more on online reviews to purchase a product. It is hard to determine whether the product is good or bad from hundreds of mixed reviews. Also, it is very time-consuming to read many reviews. So, opinion mining of reviews is necessary.
The main aim of this project is to convert the reviews of a product into a rating and to evaluate the ratings using machine learning algorithms such as Naïve Bayes and Support Vector Machine. In the process of converting the reviews to a rating, score words are created using SentiWordNet and transformed into seven categories from highly positive to highly negative
