Product Aspect Ranking using Sentiment Analysis: A Survey

A product aspect ranking framework is proposed, which automatically determine the important aspects of products from online consumer reviews, aiming at improving the usability of the countless reviews.

Abstract

In today's world, internet is the main origin of information. There are many ecommerce websites available where people discuss on different issues of product. All ecommerce website provide facility to the consumer to give opinion about their product and services. Consumer reviews contain rich and valuable knowledge for both firms and users. The problem with this information is that these reviews are mostly unorganized therefore creating difficulty for information transfer knowledge accession. We propose a product aspect ranking framework, which automatically determine the important aspects of products from online consumer reviews, aiming at improving the usability of the countless reviews. The important aspects are identified by two observations, a) The important aspects of a product are usually given by a large number of consumers; b) And consumers' opinions on the important aspects influence their overall opinions on the product. However Identifying important product aspects will increase the usability of numerous reviews and is useful to both consumers and firms. It is impractical for people to manually identify the important aspects of products from numerous reviews. Consumers can conveniently make purchasing decision by paying more attention to the important aspects, while enterprise can focus on improving the quality of these aspects and thus enhance product ranking effectively.