Fake Review Detection and Classification Using Improved Convolutional Neural Network on Amazon Dataset

Fake reviews are a growing concern for e-commerce websites and other online platforms. To tackle this issue, researchers have developed an advanced convolutional neural network system that can detect and classify fake reviews. This system has been specifically designed to analyze the Amazon review dataset, and by integrating various text pre-processing methods and an innovative attention mechanism, it has significantly improved its classification accuracy. In fact, the proposed model outperforms existing state-of-the-art techniques in terms of accuracy and F1-score, with an impressive accuracy of 0.97. These results demonstrate the effectiveness of the improved CNN model in accurately detecting and classifying fake reviews, and provide a valuable tool for maintaining the authenticity and trustworthiness of online reviews.