Automatic Detection of Fake News on Twitter by Using a New Feature: User Credibility

TitreAutomatic Detection of Fake News on Twitter by Using a New Feature: User Credibility
Publication TypeJournal Article
Year of Publication2022
AuthorsLahlou, Y, Fkihi, SE, Faizi, R
JournalLecture Notes in Networks and Systems
Volume489 LNNS
Pagination568-580
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. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85135053485&doi=10.1007%2f978-3-031-07969-6_43&partnerID=40&md5=183d4701938c5f034b79048db6ca5566
DOI10.1007/978-3-031-07969-6_43
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