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Dataset Open Access

SemEval 2019 Task 4 - Hyperpartisan News Detection

Johannes Kiesel; Martin Potthast; Maria Mestre; Rishabh Shukla; Benno Stein; David Corney; Emmanuel Vincent; Payam Adineh

Third trial dataset for the SemEval 2019 Task 4: Hyperpartisan News Detection.

The dataset contains 1 million articles. It is split in training (200,000 left, 400,000 least, 200,000 right) and validation (50,000 left, 100,000 least, 50,000 right), where no publisher that occurs in the training set also occurs in the validation set. All articles are labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.

The trial data is not fully cleaned. Due to some encoding error, some characters are replaced by question marks. However, all files are already fully compatible with the XML schema files.

Files (2.0 GB)
Name Size
article.xsd
md5:31e3fb439c98b18cd74a7d936a65b218
2.1 kB Download
articles-training-20180831.xml.zip
md5:c3e85da69f0ec76d30a2c1a0b22d3150
1.4 GB Download
articles-validation-20180831.xml.zip
md5:5dd17f5043f130407cf599d585ba4ca9
547.9 MB Download
ground-truth-training-20180831.xml.zip
md5:7ea315edde4f500b554571f388a2fa46
30.0 MB Download
ground-truth-validation-20180831.xml.zip
md5:50fdbd01f9eef4902a0e6fe93a360577
7.0 MB Download
ground-truth.xsd
md5:81dd0e153d6f78ca10a5599da6aac66e
1.6 kB Download
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