Sentiment Analysis of a Product based on User Reviews using Random Forests Algorithm

After many sentiment analysis as well as many types of methods classify the reviews that is based on test data and reviewer’s ratings which uses training., after reading reviews it is seen that star rating of reviewer do not always give a precise measure of his sentiment. This paper primarily focuses on analyzing customer reviews from the e-commerce space. Upon surveying popular e-commerce websites it can be observed that in several instances the product rating given by a customer is not consistent with the product review written by him/her. The problem is made complex by the fact that there is no standard scale to measure the rating that the user gives and the rating of the product are instinctive to the customers’ view. In several cases it is seen that a product is rated 4 out of 5. However, the reviews detail that the customer’s experience with the product is not favourable. Indeed, text reviews are a true picture of the product. To get rid of this problem, the stated system will give a boolean result i.e. whether the product is good or bad and the user does not need to read all the reviews to analyze the product.