Key points are not available for this paper at this time.
Presently, review sites are frequently confronted with the spread of wrong information, this could be done by an individual spammer or group spammers who compose fake reviews to either advertise or demean certain products that are available. This paper focuses on the detection of these fake reviews using sentiment analysis. Various data pre-processing techniques are used to convert the reviews to the proper format for analysis and for detection. The proposed methodology is to analyze reviews by making use of neural networks such as LSTM, Bi-LSTM and GRNN, and the activation functions in them namely ReLU, Sigmoid, TanH and comparing them to find the optimal model for analysis.
Rodrigues et al. (Sat,) studied this question.