An Efficient Sentiment Analysis Based on Product Reviews

Abstract

Amazon is the most popular online shopping market for most people in the world today. Anything from daily necessities to luxurious items can be bought from here. And especially in recent times where people have to avoid going out to crowded places, platforms like Amazon have emerged as the go-to solution. So, when people want to buy products from these platforms it is important for them to have a look at the reviews before being assured about it. But every product has thousands of reviews for it and it's not easy to analyze them quickly. This paper presents an implementation of a Amazon review sentiment analysis with the web application. Various algorithms are implemented for the experimentation purpose. The combination of logistic regression with CountVectorizer performed well in the term of accuracy. Using the proposed methodology, the user can search for a product on this web-based App and analysis of product reviews, price ranges, ratings and much more will be displayed to the user. The accuracy of the different algorithms is reported in this paper.