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Dataset: hyperpartisan_news_detection 🏷
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How to load this dataset directly with the πŸ€—/datasets library:

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from datasets import load_dataset dataset = load_dataset("hyperpartisan_news_detection")


Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4. Given a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person. There are 2 parts: - byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed. - bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or


  title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},
  author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},

Models trained or fine-tuned on hyperpartisan_news_detection

None yet. Start fine-tuning now =)