Table 2.

Fake news detection studies made by using ANN-based supervised learning algorithms.

Refs.	Dataset	ML	Success ML	Performance measure	Best result
[79]	Kaggle open source dataset of fake	LR, RNN, GRU,	GRU	F1-score	0.84
	news article and signalmedia open	LSTM, BiLSTM,
	source dataset of not fake news article.	CNN
[80]	Using a set of articles flagged as false by	KNN, SVM,	LSTM	F1-score	0.90
	Snopes, and a set of real articles from news	LSTM
	organizations such as NDTV, CNN etc..
[81]	FNC-1 open source dataset of articles	LSTM, GRU	GRU	FNC-score	69.08
[82]	The form of (headline, body) pairs from	RNN, LSTM,	BiLSTM	Accuracy	0.84
	leading news organizations such as	BiLSTM, GRU,
	NDTV, CNN etc..	BiGRU
[83]	FNC-1 open source dataset of articles.	MLP	MLP	FNC-score	83.08
[84]	Tweets on Twitter, discussion topics	CSI, DT, SVM,	CSI	Accuracy	0.95
	on Weibo and users.	LSTM, GRU
[85]	19 fake news article websites (20,372 article)	3HAN, GRU	3HAN	Accuracy	0.97
	labeled by polifact, 9 real news article
	websites (20,932 article) listed by forbes.
[86]	Tweets from 174 suspicious propaganda accounts	LR, RNN,	RNN, CNN	F1-score	0.92
	identified by PropOrNot and manually constructed	CNN
	a list of 252 trusted news accounts by writers.
[87]	LIAR open source dataset of articles.	LR, SVM,	CNN	Accuracy	0.27
		BiLSTM, CNN
[88]	LIAR open source dataset of articles.	LR, SVM, RNN,	CNN	Accuracy	0.27
		GRU, LSTM,
		Bi-LSTM, CNN
[89]	Open source dataset from	GRU, LSTM, BiLSTM,	SMHA-CNN	F1-score	0.96
	fakenews.mit.edu.	SMHA-CNN