Mining Of Customer Review Feedback Using Sentiment Analysis For Smart Phone Product - et. al., Dr.P.Suresh, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
With the fast growth of e-commerce, large number of products is sold online, and a lot more people are purchasing products online. People also give feedback of product purchased in form of reviews. The user generated reviews for products and services are largely available on internet. To extract the valuable understanding, classification of reviews is required from a huge set of feedback which has converted into positive and negative sentiments. The process of Sentiment Analysis (SA) has mined the attitude, opinions and emotions spontaneously from text, speech and database via Natural Language Process (NLP).It contains feedback review about product, product features or some sentiment emotional views on the product given by the customer. In this research work, feedback from the customer which associated with smart phones is taken from Amazon.com in order to predict the rating of the product given by the user feedback using SA. Feedback review of the customers has been collected fromAmazon.com and this research work had nearly 4000customer feedback reviews based on related categories namely ID of the product, name of the product, name of the brand, Rating, review of the product and vote based on review. This kind of analysis will be helpful for the customers to identify the better product with quick analysis and identify the implicit product perhaps the e-commerce business to improve the sales based on providing offers for particular implicit products.