Arabic fake news detection in social media Based on AraBERT
21st IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2022
; : 214-220, 2022.
Article
in English
| Scopus | ID: covidwho-2321950
ABSTRACT
Social media has become a source of information for many people because of its freedom of use. As a result, fake news spread quickly and easily, regardless of its credibility, especially over the past decade. The vast amount of information being shared has fraudulent practices that negatively affect readers' cognitive abilities and mental health. In this study, we aim to introduce a new Arabic COVID-19 dataset for fake news related to COVID-19 from Twitter and Facebook. Afterward, we applied two pre-Trained models of classification AraBERT and BERT base Arabic. As a result, AraBERT models obtained better accuracy than BERT base Arabic in two datasets. © 2022 IEEE.
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Database:
Scopus
Language:
English
Journal:
21st IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2022
Year:
2022
Document Type:
Article
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