(5)

FPR =

VII. CHALLENGES AND RESEARCH DIRECTION
Despite the fact that numerous studies have been conducted
on the identiﬁcation of fake news, there is always space
for future advancement and investigation. In the sense of
recognizing fake news, we highlight challenges and sev-
eral unique exploration areas for future studies. Although
DL-based methods provide higher accuracy compared to the
other methods, there is scope to make it more acceptable.
• The feature and classiﬁer selection greatly inﬂuences the
efﬁciency of the model. Previous studies did not place
a high priority on the selection of features and classi-
ﬁers. Researchers should focus on determining which
classiﬁer is most suitable for particular features. The
long textual features require the use of sequence models
(RNNs), but limited research works have taken this into
account. We believe that studies that concentrate on the
selection of features and classiﬁers might potentially
improve performance.
A_Comprehensive_Review_on_Fake_News_Detection_With_Deep_Learning