Process / pipeline

Fake News Detection — Misinformation Classification

Fake news detection is a natural-language-processing classification task that assesses the credibility of news text and labels content as fake or genuine. Building on the social-media framing of Shu et al. (2017) and the automated-fact-checking framing of Thorne and Vlachos (2018), it turns unstructured news articles into a supervised credibility decision learned from labelled examples.

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Sources

  1. Shu, K. et al. (2017). Fake News Detection on Social Media. ACM SIGKDD. link
  2. Thorne, J. & Vlachos, A. (2018). Automated Fact Checking. COLING. link

Related methods

Referenced by

ScholarGateFake News Detection (Fake News Detection (Misinformation Classification)). Retrieved 2026-06-04 from https://scholargate.app/tr/text-mining/fake-news-detection