Fake Review Detector and Price Analysis

The process of using online product reviews and their prices during purchasing has become widespread over the years. Nevertheless, the accuracy of such data cannot be guaranteed due to fake reviews and concealed prices. Therefore, this research proposes an approach that may help solve the stated problems. Indeed, in the current world, people tend to depend more on online reviews and prices when making purchases online. But the emerging problem is that fake reviews and misleading pricing have become common practices nowadays. For this reason, a new method is proposed which consists of the integration of web scraping technology and AI models including transformers and large language models. The system operates through two main stages. The first stage involves extracting real-time information from e-commerce platforms. The second stage consists of employing the refined AI algorithm to detect suspiciously written review texts. Simultaneously, prices will be monitored to provide the most cost-effective offers and detect any irregular price spikes. To simplify the operation of the algorithm and make its output understandable by any user, our system is supplemented with an LLM that gives recommendations on buying products.