A Novel Sentiment Classification of Product Reviews using Levenshtein Distance

Abstract

E-commerce platform has brought about a revolutionary change in the way people conduct shopping. In India, the number of digital buyers in 2016 was 130.4 million and by 2021 the number is estimated to increase to around 400 million. In this paper we propose a Levenshtein distance based sentiment classification engine that reads the reviews across different websites for a given product, eventually providing a metric that would help the user in making an informed choice of product.