Abstract:
"In the digital age, the growing in reviews with disinformation poses a significant challenge to businesses and consumers alike. Identifying and preventing disinformation in online customer reviews is crucial for maintaining trust and integrity in review platforms. This project addresses the need for a more robust and effective disinformation detection system, focusing on real-time comparison features for restaurant customer reviews.
The project aims to design, develop, and evaluate ""Reveal,"" a browser extension that analyzes and compares customer reviews on Google Maps. By leveraging natural language processing (NLP) techniques, ""Reveal"" summarizes reviews, compares them with user-inputted reviews, and provides a similarity percentage, enabling users to detect disinformation easily.
The findings of this project demonstrate the effectiveness of ""Reveal"" in detecting disinformation, providing a valuable tool for businesses and consumers to navigate the complex landscape of online reviews. By enhancing transparency and trust in online reviews, ""Reveal"" contributes to a more reliable and trustworthy online review ecosystem.
This project is important as it addresses the growing concern of fake reviews, which can influence consumer decisions and business reputations. ""Reveal"" offers a practical solution to a pressing problem, highlighting the significance of preventing disinformation in online reviews."
