An empirical study: automating e-commerce product rating through an analysis of customer review

• Main Authors: Rajendran, Uvaaneswary, Abdullah, Salfarina, Aziz, Khairi Azhar, Anuar, Sazly
• Format: Article
• Published: The Science and Information Organization (SAI) 2023
• Online Access: http://psasir.upm.edu.my/id/eprint/106551/; https://thesai.org/Publications/ViewPaper?Volume=14&Issue=11&Code=IJACSA&SerialNo=12

e-Commerce today is a remarkable experience. However, finding and purchasing a right quality product based on numerous product reviews and manual rating in the e-commerce websites utilize much time among the consumers. This paper presents the problems faced by the consumers when buying products in e-commerce websites and a solution to solve the problems. Thus, the idea of an automated product rating system would be very useful for the consumers in which it rates the products automatically based on the reviews given by the buyers. To do this, a technique called Sentiment Analysis is used. It also ranks the products in order based on the product rating that is generated automatically. It would provide a way for the consumers to purchase their desired product within minutes. Surveys and interviews were conducted to find out the problems faced by consumers when purchasing a product online through e-commerce websites. There was also research conducted to study the product rating and product review section on the current e-commerce websites. To conclude, this automated product rating system eventually eases the consumers effort and time from reading numerous reviews and trusting inaccurate product rating to find a best quality product for them.