ICTMCG/GenFEND

Let Silence Speak: Enhancing Fake News Detection with Generated Comments from Large Language Models, CIKM 2024.

24
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Experimental

This project helps social media analysts and misinformation researchers identify fake news more effectively. It takes news articles or social media posts, along with generated virtual comments from large language models, and outputs a classification indicating whether the content is fake or real news. Social media platform moderators and content integrity teams would find this useful for improving their detection systems.

No commits in the last 6 months.

Use this if you need to improve the accuracy of your fake news detection systems, especially when real user comments are scarce or unavailable.

Not ideal if you primarily work with image or video-based misinformation, as this tool focuses on text-based content and its associated comments.

misinformation-detection social-media-analysis content-moderation fact-checking information-integrity
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 8 / 25
Community 9 / 25

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32

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3

Language

Python

License

Last pushed

Mar 15, 2025

Commits (30d)

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