• DocumentCode
    3301263
  • Title

    Sentiment and sentimental agent identification based on sentimental sentence dictionary

  • Author

    Liu, Dong ; Quan, Changqin ; Ren, Fuji ; Chen, Peng

  • Author_Institution
    Res. Center of Sci. & Technol., Beijing Univ. of Posts & Telecommun., Beijing
  • fYear
    2008
  • fDate
    19-22 Oct. 2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents a method of sentiment and sentimental agent identification based on Chinese sentimental sentence dictionary. Our method can identify eight kinds of sentiment (including joy, sorrow, love, disgust, surprise, anxiety, anger and hate), and the main sentimental agent. Sentimental sentence dictionary is composed by some sentimental sentence patterns. And the sentiment of a candidate sentence is identified by calculating the consistency with the sentimental sentence patterns. Especially, using the sentimental sentence dictionary, we can get rid of the sentences without sentiment, but have sentimental words. According to sentiment words and expressions, the sentences which are not appeared in the sentimental sentence dictionary also can be identified. The experiments show that we can get precision of 84% for sentiment identification, and precision of 69% for sentimental agent identification.
  • Keywords
    data mining; dictionaries; natural language processing; text analysis; word processing; Chinese sentimental sentence dictionary; sentiment agent identification; sentimental agent identification; sentimental sentence patterns; Dictionaries; Information science; Intelligent agent; Intelligent systems; Laboratories; Man machine systems; Publishing; Robots; Systems engineering and theory; Telecommunication computing; Sentiment identification; sentimental agent identification; sentimental sentence dictionary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Language Processing and Knowledge Engineering, 2008. NLP-KE '08. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4515-8
  • Electronic_ISBN
    978-1-4244-2780-2
  • Type

    conf

  • DOI
    10.1109/NLPKE.2008.4906802
  • Filename
    4906802