Artificial Intelligence and Communication Technologies
Fake Review Detection using Deep Learning
Authors: Sangeetha S, Sangeetha B, Raja Kumar I, Shevannth R, Krishna Prasath S and Mohammed Rafi M
Publishing Date: 11-02-2023
ISBN: 978-81-955020-5-9
Abstract
In recent times online shopping has evolved rapidly, but finding a quality product in such a complex network is not a simple task. Internet reviews help users to find relevant items. But there is a high magnitude of fake internet reviews available online. So distinguishing fake and true reviews is an important task for both customers and suppliers. Because in the customer perspective they require a quality product and in the supplier perspective, they need to sell their product. Generally, positive reviews on a targeted product would increase its sales. To determine fake reviews this paper compares the reviews of several reviewers from Yelp dataset of restaurants and proposes a deep learning approach to detect fake reviews. The proposed deep learning model is tested with benchmarked datasets and results are evaluated. The experimental results show improved performance compared to the existing deep learning models.
Keywords
Fake Review, Deep Learning, CNN, Bi Directional LSTM, Yelp Dataset.
Cite as
Sangeetha S, Sangeetha B, Raja Kumar I, Shevannth R, Krishna Prasath S and Mohammed Rafi M, "Fake Review Detection using Deep Learning", In: Saroj Hiranwal and Garima Mathur (eds), Artificial Intelligence and Communication Technologies, SCRS, India, 2023, pp. 655-668. https://doi.org/10.52458/978-81-955020-5-9-62