News’ Credibility Detection on Social Media Using Machine Learning Algorithms

Authors

Farah Yasser, Business Information Systems, Faculty of Commerce and Business Administration, Helwan University, EgyptFollow
Sayed AbdelMawgoud, Information Systems Department, Helwan University, EgyptFollow
Amira M. Idrees AMI, Future University in EgyptFollow

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%

Recommended Citation

Yasser, Farah; AbdelMawgoud, Sayed; and Idrees, Amira M. AMI (2023) "News’ Credibility Detection on Social Media Using Machine Learning Algorithms," Future Computing and Informatics Journal: Vol. 8: Iss. 1, Article 2.
Available at: https://digitalcommons.aaru.edu.jo/fcij/vol8/iss1/2