Aspect Based Sentiment Classification and Contradiction Analysis of Product Reviews

Abstract

Due to the rapid growth of Internet infrastructure and E-Commerce, people can easily buy different products from different E-commerce websites. The reviews posted by the customers in the E-commerce websites can help us to get an idea about the products. It also helps us to identify the behavior of the individuals. This is because users’ reviews on items are inevitably dependent on many social effects such as peer influence, user profile information, user preference etc. Considering this fact, in this paper, we present a framework to analyze users’ reviews about the products to identify various aspects of the products listed online. In our approach, we use a large volume of publicly available product review data and perform different experiments. Experimental results show that our system provides better performance in case of negative aspect.