Multilingual Review Validation System

Online platforms face challenges in handling fraudulent or misleading reviews, particularly when dealing with content written in multiple languages. This project introduces an AI-based approach designed to validate reviews across different languages by utilizing advanced natural language processing (NLP) and machine learning techniques. A classification model is trained to distinguish between genuine and spam reviews with high accuracy. The system is deployed within a web-based application built using the Flask framework, providing users with a straightforward interface to submit reviews for validation. By offering instant feedback on review authenticity, the platform enhances trust, supports better decision-making for consumers, and aids businesses in maintaining credibility. This work demonstrates the effectiveness of integrating machine learning with web technologies to deliver scalable, user-friendly, and multilingual solutions for review management. With the rapid growth of online platforms, the authenticity of user-generated reviews has become a critical concern, especially when they are written in multiple languages. Natural Language Processing (NLP) and machine learning techniques have shown strong capabilities in analyzing and classifying textual data across diverse linguistic contexts.