• DocumentCode
    1909931
  • Title

    Extracting the Opinions of News Articles based on Emotionally Laden Words

  • Author

    Shinomiya, Mizuho ; Ren, Fuji ; Kuroiwa, Shingo ; Tsuchiya, Seiji

  • Author_Institution
    Grad. Sch. of Adv. Technol. & Sci., Tokushima Univ., Tokushima
  • fYear
    2007
  • fDate
    Aug. 30 2007-Sept. 1 2007
  • Firstpage
    262
  • Lastpage
    267
  • Abstract
    In this paper we propose an approach to extract the opinion of the media from news articles based on emotionally laden words. In the propose approach, the opinions are judged by the total number of the emotion levels from articles. The emotion level is the number from -3 to +3 that indicate emotionally laden words whether have plus or minus images. The articles of baseball game and the editorial article are used as experiment object. The precision of the propose approach on the articles about baseball game is 66%, and on the articles of political event is 36%.
  • Keywords
    information retrieval; baseball game; emotionally laden words; news articles; opinions extraction; political event; Blogs; Data mining; Frequency; Internet; Paper technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Language Processing and Knowledge Engineering, 2007. NLP-KE 2007. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-1610-3
  • Electronic_ISBN
    978-1-4244-1611-0
  • Type

    conf

  • DOI
    10.1109/NLPKE.2007.4368041
  • Filename
    4368041