Table 1.

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

Refs.	Dataset	ML	Success ML	Performance measure	Best result
[10]	Mobile phone reviews from mobile01.com	LR, SVM	SVM	F1-score	0.61
[74]	Hotel reviews, restaurant review, gay marriage, and gun control,	SGD, SVM,	SVM	Accuracy	0.9
	fake and real news articles from kaggle.com	KNN, LR, DT
[75]	3 large Facebook pages each from the right and from the left	NB	NB	Accuracy	0.75
	and Facebook pages of Politico, CNN and ABC News
[76]	The authors present a list of Facebook pages divided into two	LR,	HBLC	Accuracy	0.99
	categories: scientific news sources and conspiracy news sources.	HBLC
[11]	Articles on sport, politics, rumor, health and other were	SVM,	SVM	F1-score	0.79
	collected with web crawler.	NB
[77]	2 satirical news sites (The Onion and The Beaverton) and 2 legitimate	SVM	SVM	F1-score	0.87
	news sources (The Toronto Star and The New York Times): varying
	across 4 domains (civics, science, business, and “soft” news)
[78]	Collecting legitimate news from mainstream news websites such as	SVM	SVM	F1-score	0.73
	CNN, FoxNews, Bloomberg, and CNET and collecting fake
	news using crowdsourcing.
[9]	News articles from Google with web crawler	NB	NB	Accuracy	0.79