Fake review detection using natural language processing (NLP) techniques - Pyae Sone Khin (Nanyang Technological University, 2024)
Detecting fake reviews is important for maintaining the authenticity and reliability of online platforms. In this project, we address the challenges of fake review detection using machine learning techniques, focusing on the application of DistilBERT model and adversarial sample generation. Our approach involves data preprocessing, which includes cleaning and augmentation, to ensure the quality and diversity of the dataset. This project used state-of-the-art technologies and modern tools to train and fine-tune the model and evaluate the performance in terms of precision, recall, F1-score, and accuracy.