A Review of Fake News Detection Techniques for Arabic Language

Abstract

The growing proliferation of social networks provides users worldwide access to vast amounts of information. However, although social media users have benefitted significantly from the rise of various platforms in terms of interacting with others, e.g., expressing their opinions, finding products and services, and checking reviews, it has also raised critical problems, such as the spread of fake news. Spreading fake news not only affects individual citizens but also governments and countries. This situation necessitates the immediate integration of artificial intelligence methodologies to address and alleviate this issue effectively. Researchers in the field have leveraged different techniques to mitigate this problem. However, research in the Arabic language for fake news detection is still in its early stages compared with other languages, such as English. This review paper intends to provide a clear view of Arabic research in the field. In addition, the paper aims to provide other researchers working on solving Arabic fake news detection problems with a better understanding of the common features used in extraction, machine learning, and deep learning algorithms. Moreover, a list of publicly available datasets is provided to give an idea of their characteristics and facilitate researcher access. Furthermore, some of limitations and challenges related to Arabic fake news and rumor detection are discussed to encourage other researchers.