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Data · dataset · 2022

HyperpartisanNewsDetection

Listed in Hugging Face Datasets

Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.

Description

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 MediaBiasFactCheck.com.

Links

Topics

Stated by source
text classification
Inferred from text
Text 75%
Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
Hugging Face DatasetsSemEvalWorkshop/hyperpartisan_news_detection14 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].local:modality:textenrichment · Hugging Facekeyword-concept-rules@1.0.0title+description (75%)
concepts[task].hf_task:text-classificationsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
licensesource · Hugging Faceconnector:huggingface@1.0.0/tags[license:*]
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0