Unsupervised fake news detection on social media using hybrid Gaussian Mixture Model.

ABSTRACT: The rise of social media has revolutionized information dissemination, creating new opportunities but also significant challenges. One such challenge is the proliferation of fake news, which undermines the credibility of journalism and contributes to societal unrest. Manually identifying fake news is impractical due to the vast volume of content, prompting the development of automated systems for fake news detection. This challenge has motivated numerous research efforts aimed at developing automated systems for fake news detection. However, most of these approaches rely on supervised learning, which requires significant time and effort to construct labeled datasets. While there have been a few attempts to develop unsupervised methods for fake news detection, their reported accuracy result

SUBMITTER: Perveen S 

PROVIDER: S-EPMC12360590 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature