Web proceedings papers

Authors

Goran Graorkovski , Martina Toshevska and Georgina Mirceva

Abstract

Technological advancement and broad social media usage have increased the reliance on news sources as the main information source. As a result, it is critical to counter the dissemination of false information and fake news. The desire for fame and more website traffic is a common driving force behind the publication of fake news. But this incorrect information has negative effects sometimes. Fake news is widely propagated through social media sites such as Facebook, Twitter, Instagram, YouTube, and TikTok. Many techniques have been developed to filter and spot fraudulent material on the web and social media. The online experience for frequent internet users can be improved by taking action against those who post and distribute dangerous and fake information. This research examines many academic works on effective and popular techniques for spotting false news. This paper discusses the nature of fake news, its potential harm, and fundamental methods for detecting it.

Keywords

Fake news detection, Misinformation, Machine learning, Deep learning