yaqingwang/WeFEND-AAAI20
Dataset for paper "Weak Supervision for Fake News Detection via Reinforcement Learning" published in AAAI'2020.
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.
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Jul 29, 2020
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