An Arabic Corpus of Fake News: Collection, Analysis and Classification - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2019

An Arabic Corpus of Fake News: Collection, Analysis and Classification

Résumé

Over the last years, with the explosive growth of social media, huge amounts of rumors have been rapidly spread on the internet. Indeed, the proliferation of malicious misinformation and nasty rumors in social media can have harmful effects on individuals and society. In this paper, we investigate the content of the fake news in the Arabic world through the information posted on YouTube. Our contribution is threefold. First, we introduce a novel Arab corpus for the task of fake news analysis, covering the topics most concerned by rumors. We describe the corpus and the data collection process in detail. Second, we present several exploratory analysis on the harvested data in order to retrieve some useful knowledge about the transmission of rumors for the studied topics. Third, we test the possibility of discrimination between rumor and no rumor comments using three machine learning classifiers namely, Support Vector Machine (SVM), Decision Tree (DT) and Multinomial Naïve Bayes (MNB).
Fichier principal
Vignette du fichier
MaysoonICALP2019.pdf (133.66 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02314246 , version 1 (11-10-2019)

Identifiants

Citer

Maysoon Alkhair, Karima Meftouh, Nouha Othman, Kamel Smaïli. An Arabic Corpus of Fake News: Collection, Analysis and Classification. Arabic Language Processing: From Theory to Practice 7th International Conference, ICALP 2019, Nancy, France, October 16–17, 2019, Proceedings, Communications in Computer and Information Science book series (CCIS, volume 1108), pp.292-302, 2019, ⟨10.1007/978-3-030-32959-4_21⟩. ⟨hal-02314246⟩
713 Consultations
1258 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More