Product Aspect Ranking Using Sentimental Analysis

E-commerce is a digital-platform where people can buy and sell things online. E-commerce allows the customers to purchase products anytime and from anywhere. It also gives the consumers the privilege to review positively or negatively on any product over the platform. Since people acknowledge the online reviews as an important information on product, it helps the customer in making decision. User reviews are their feedback on a particular product or service. In this paper, the aspect-based sentiment analysis is performed. The reviews are pre-processed and then polarity is determined using sentiment analysis. Sentiment classification is done using naïve bayes (NB) and support vector machine (SVM) algorithm classifies the reviews into positive or negative ones. Then the ranking is done by the ranking algorithm based on their importance.