Nicozwy/CofCED

COLING 2022: A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detection.

42
/ 100
Emerging

This project helps media analysts and content moderators identify fake news by analyzing raw reports and public reactions, rather than relying solely on fact-checked reports. It takes in collections of user-generated reports and claims and outputs a judgment on the claim's veracity with explanations. This is intended for professionals who need to quickly assess information reliability in dynamic online environments.

102 stars.

Use this if you need an automated system to detect fake news and understand why a claim is flagged, especially when formal fact-checks are not yet available.

Not ideal if you require a system that only processes pre-vetted, expert-reviewed fact-checks rather than leveraging community input.

fake-news-detection content-moderation media-analysis public-sentiment-analysis misinformation-tracking
No Package No Dependents
Maintenance 10 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 7 / 25

How are scores calculated?

Stars

102

Forks

5

Language

Python

License

Apache-2.0

Last pushed

Feb 03, 2026

Commits (30d)

0

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