148 DL-based studies were examined to provide a detailed
description of these architectures: CNN in section V-A and
RNN in Section V-B, Graph Neural Network in Section V-C,
Generative Adversarial Network in Section V-D, Attention
Mechanism in Section V-E, Bidirectional Encoder Repre-
sentations for Transformers in Section V-F, and Ensemble
Approach in Section V-G.

A. CONVOLUTIONAL NEURAL NETWORK (CNN)
A few deep learning models have been introduced to handle
ambiguous detection issues. CNNs and RNNs are the most
interesting models [77]. Researchers are trying to boost the
performance of the fake news detector with CNN by taking
its power of extracting features well and better classiﬁcation
process [132]. However, CNNs are also gaining popularity

156158

VOLUME 9, 2021

M. F. Mridha et al.: Comprehensive Review on Fake News Detection With Deep Learning
A_Comprehensive_Review_on_Fake_News_Detection_With_Deep_Learning