Abstract

In the digital age, the widespread dissemination of misinformation and fake news poses significant threats to public opinion, social trust, and decision-making processes. This survey provides a comprehensive overview of recent advances in fake news detection, with a particular focus on techniques involving preprocessing, text representation, and classification. We further examine related tasks such as claim detection and veracity prediction, which form the backbone of automated fact-checking systems. The survey also explores some of the Arabic fake news detection datasets that have been published for various tasks. This work aims to offer valuable insights into current research trends, identify existing challenges, and highlight potential directions for future developments in the fight against misinformation.

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