Comments and Feedback Verification System using Large Language Model
Akshay Kumar Kushwaha, Shreya Jadon, Preet Kamal, Madan Lal Saini, Vijay Mohan Shrimal · 2024
In recent years, the rapid expansion of digital platforms has resulted in a substantial rise in user-generated content, especially comments and feedback. For increasing traffic on website and selling products people uses fake reviews. Verifying the authenticity and relevance of this content is essential for preserving the integrity of online communities and enhancing user experience. This paper introduces an innovative system for verifying comments and feedback using large language models (LLMs). The proposed system employs advanced natural language processing (NLP) techniques and pretrained LLM models to analyze and verify the content of user comments and feedback. This advance feedback verifier system helps to figure out either comments are real or fake for e-commerce websites. Our experimental results show the effectiveness of the proposed system in various real-world situations, demonstrating its potential to greatly enhance content moderation processes and promote healthier online interactions. This system can also understand personalized recommendations about any product and it could be a great step towards making purchasing decision.