Abstract—In today’s world, the significance of online shopping is growing day by day. The business ideas have been refashioned and completely transformed by making it so easy for the customers to purchase anything they want at just one click of a mouse button. It is becoming even more popular due to its high level of convenience. The only thing customers must have been the Internet and the appropriate method of payment. Amazon.com is one such widely known E-commerce website and it is being used worldwide. It was initially known for its huge collection of books but later it was expanded to sell electronics and other home appliances and consumer products. At present, Amazon is known to sell millions of products. This growth of E-commerce gave importance to customer needs and opinions which in turn gave rise to an important aspect of online shopping known as ‘User Reviews’. User reviews are customer suggestions and opinions about the product which helps other customers make decisions about that product. Such review systems form the backbone of E-commerce. The goal of this project is to understand and analyze the Amazon User Review Dataset with the help of different visualization techniques. These visualization techniques will help showcase various informative statistical trends which will provide us with insights about the Amazon Review system. These insights will help in exploring the possible improvements that can be done to satisfy the customers. Major work will involve empirical analysis for data understanding and exploration by taking into consideration, the various metrics related to the user reviews as opposed to sentimental analysis on the review text which aims at understanding the overall emotion of the reviews which has been done previously.
Index Terms—Sentiment analysis, chi-square, tableau, dataset, raw data, correlation, hypothesis, business intelligence.
Aamir Rashid was with the School of Computer Science & Technology, Kean University, Union, NJ 07083, USA (e-mail: rashida@kean.edu).
Ching-yu Huang is with the School of Computer Science & Technology, Kean University, Union, NJ 07083, USA (e-mail: chuang@kean.edu).
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Cite:Aamir Rashid and Ching-yu Huang, "Sentiment Analysis on Consumer Reviews of Amazon Products," International Journal of Computer Theory and Engineering vol. 13, no. 2, pp. 35-41, 2021.
Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
