Detecting Online Review Fraud Using Sentiment Analysis - Presentation by Bryn Caron, recent Graduate of Minnesota State University, Mankato
Wednesday, April 20, 2022
5:00 PM - 6:00 PM
Online via Zoom
With the exponential increase in e-commerce, online reviews have become integral to the marketing of products and services. Customers are inclined to buy products and services that have received high ratings and positive reviews. Consequently, fake reviews are increasingly becoming a way to mislead customers into trusting, or mistrusting, the credibility and reliability of a product or service. Though online fake reviews have garnered some attention from the media and research communities, there is a need for effective technical solutions for detecting, and therefore mitigating, fraudulent reviews to improve consumer confidence in e-commerce. The purpose of this study is to explore the use of natural language processing techniques in detecting fake online reviews. We analyze the text of online reviews for various book titles. We investigate the accuracy of the polarity score, a common metric used in sentiment analysis, in the context of the star rating of the reviews. Our findings conclude that the polarity score is not a reliable measure for detecting fake reviews. In addition, the study sheds light on the limitations of sentiment analysis in detecting fake reviews.