yaqingwang/WeFEND-AAAI20

Dataset for paper "Weak Supervision for Fake News Detection via Reinforcement Learning" published in AAAI'2020.

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Emerging

This dataset helps researchers and data scientists working on automated fake news detection. It provides news articles, their associated publisher accounts, URLs, image URLs, and user reports. The primary output is a labeled dataset where each news item is marked as either real or fake, along with a large collection of unlabeled news to help train and test models designed to identify misinformation.

139 stars. No commits in the last 6 months.

Use this if you are developing or evaluating machine learning models to automatically identify fake news, especially when looking for datasets that incorporate user reports as a form of weak supervision.

Not ideal if you are looking for a tool or application for immediate fake news identification, as this is a dataset for model development, not an end-user solution.

misinformation-detection social-media-analysis natural-language-processing data-science-research
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 20 / 25

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Stars

139

Forks

27

Language

Jupyter Notebook

License

Last pushed

Jul 29, 2020

Commits (30d)

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