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News' Credibility Detection on Social Media Using Machine Learning Algorithms.

Authors :
Yasser, Farah
AbdelMawgoud, Sayed AbdelGaber
Idrees, Amira M.
Source :
Future Computing & Informatics Journal; 2023, Vol. 8 Issue 1, p21-31, 11p
Publication Year :
2023

Abstract

Social media is essential in many aspects of our lives. Social media allows us to find news for free. anyone can access it easily at any time. However, social media may also facilitate the rapid spread of misleading news. As a result, there is a probability that low-quality news, including incorrect and fake information, will spread over social media. As well as detecting news credibility on social media becomes essential because fake news can affect society negatively, and the spread of false news has a considerable impact on personal reputation and public trust. In this research, we conducted a model that detects the credibility of Arabic news from social media; particularly Arabic tweets. The content of the tweets revolves around the COVID-19 pandemic. The proposed model applied to detect news credibility using text mining techniques and one of the well-known machine learning classifiers, Decision tree which has the best accuracy equal to 86.6%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23147288
Volume :
8
Issue :
1
Database :
Complementary Index
Journal :
Future Computing & Informatics Journal
Publication Type :
Academic Journal
Accession number :
167358435
Full Text :
https://doi.org/10.54623/fue.fcij.8.1.2