@article {Lahlou2022568,
	title = {Automatic Detection of Fake News on Twitter by Using a New Feature: User Credibility},
	journal = {Lecture Notes in Networks and Systems},
	volume = {489 LNNS},
	year = {2022},
	note = {cited By 0},
	pages = {568-580},
	abstract = {Nowadays, searching news on social media like Twitter or Facebook is something usual. Any internet users can create a lot of content: posts, comments, and they can also redistribute information with retweet option for example. Nevertheless, a large portion of these pieces of news is fake and its main aim is simply to mislead people. In this case, information credibility on social networks is an increasing important issue. This article develops a method to automatically detect fake news on Twitter by calculating a user credibility. Many approaches uses NLP techniques to analyse the content of tweets to predict the credibility of news. Our approach is based on social context feature; we propose a new feature user credibility. {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
	doi = {10.1007/978-3-031-07969-6_43},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135053485\&doi=10.1007\%2f978-3-031-07969-6_43\&partnerID=40\&md5=183d4701938c5f034b79048db6ca5566},
	author = {Lahlou, Y. and Fkihi, S.E. and Faizi, R.}
}
