Contrasting opposing views of news articles on contentious issues

  • Souneil Park*
  • , Kyung Soon Lee
  • , Junehwa Song
  • *Corresponding author for this work

    Research output: Contribution to conferenceConference paperpeer-review

    Abstract

    We present disputant relation-based method for classifying news articles on contentious issues. We observe that the disputants of a contention are an important feature for understanding the discourse. It performs unsupervised classification on news articles based on disputant relations, and helps readers intuitively view the articles through the opponent-based frame. The readers can attain balanced understanding on the contention, free from a specific biased view. We applied a modified version of HITS algorithm and an SVM classifier trained with pseudo-relevant data for article analysis.

    Original languageEnglish
    Title of host publicationACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics
    Subtitle of host publicationHuman Language Technologies
    Pages340-349
    Number of pages10
    StatePublished - 2011
    Event49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-HLT 2011 - Portland, OR, United States
    Duration: 2011.06.192011.06.24

    Publication series

    NameACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies
    Volume1

    Conference

    Conference49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-HLT 2011
    Country/TerritoryUnited States
    CityPortland, OR
    Period11.06.1911.06.24

    Quacquarelli Symonds(QS) Subject Topics

    • Linguistics

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