Review of Efficient Methods for Sentiment Analysis of E-Commerce Customer Review using Machine Learning Techniques

The buying behavior on an E-Commerce website is overly influenced by the type of customer reviews the product receives. Increasing volume of online shopping has caused the consumer rely highly on the opinions of the other customers when making purchase decision. Not just the individual review but also the volume of reviews has an impact on the customer. However, it can be challenging for the customer as well as the businesses to analyze all these reviews to make a decision. This problem could be solved by classifying these reviews with the help of various machine learning methods by analyzing their sentiments in three different categories namely, positive, neutral and negative sentiments, which could be done using the subjective text on the web. This research paper explores various predictive models like machine learning, deep learning, transfer learning, etc. and covers the techniques and approaches for sentiment analysis of e-commerce customer review using machine learning, and find out the most efficient one of all whiles finding out the enhancement that could be made into them.