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SemEval 2019 Task 4 - Hyperpartisan News Detection

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


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  <identifier identifierType="DOI">10.5281/zenodo.1406208</identifier>
  <creators>
    <creator>
      <creatorName>Johannes Kiesel</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-1617-6508</nameIdentifier>
      <affiliation>Bauhaus-Universität Weimar</affiliation>
    </creator>
    <creator>
      <creatorName>Martin Potthast</creatorName>
      <affiliation>Leipzig University</affiliation>
    </creator>
    <creator>
      <creatorName>Maria Mestre</creatorName>
      <affiliation>Factmata Ltd.</affiliation>
    </creator>
    <creator>
      <creatorName>Rishabh Shukla</creatorName>
      <affiliation>Factmata Ltd.</affiliation>
    </creator>
    <creator>
      <creatorName>Benno Stein</creatorName>
      <affiliation>Bauhaus-Universität Weimar</affiliation>
    </creator>
    <creator>
      <creatorName>David Corney</creatorName>
    </creator>
    <creator>
      <creatorName>Emmanuel Vincent</creatorName>
      <affiliation>Factmata Ltd.</affiliation>
    </creator>
    <creator>
      <creatorName>Payam Adineh</creatorName>
      <affiliation>Bauhaus-Universität Weimar</affiliation>
    </creator>
  </creators>
  <titles>
    <title>SemEval 2019 Task 4 - Hyperpartisan News Detection</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2018</publicationYear>
  <subjects>
    <subject>Hyperpartisan news</subject>
    <subject>SemEval</subject>
    <subject>SemEval 2019</subject>
    <subject>SemEval 2019 Task 4</subject>
    <subject>Biased news</subject>
    <subject>News bias</subject>
    <subject>Hyperpartisan</subject>
    <subject>Hyperpartisanship</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2018-09-03</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1406208</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://pan.webis.de/semeval19/semeval19-web/</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1310145</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/pan</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/webis</relatedIdentifier>
  </relatedIdentifiers>
  <version>Trial v3</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Third trial dataset for the SemEval 2019 Task 4: Hyperpartisan News Detection.&lt;/p&gt;

&lt;p&gt;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 &lt;strong&gt;no&lt;/strong&gt; 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.&lt;/p&gt;

&lt;p&gt;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.&lt;/p&gt;</description>
  </descriptions>
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