• DocumentCode
    1921527
  • Title

    Sentiment classification using phrase patterns

  • Author

    Fei, Zhongchao ; Liu, Jian ; Wu, Gengfeng

  • Author_Institution
    Dept. of Comput. Sci., Shanghai Univ., China
  • fYear
    2004
  • fDate
    14-16 Sept. 2004
  • Firstpage
    1147
  • Lastpage
    1152
  • Abstract
    This paper presents a phrase pattern-based method in classifying sentiment orientation of text. That is to analyze whether the text expresses a favorable or unfavorable sentiment for a specific subject. In our method, we construct some phrase patterns and calculate their sentiment orientation by unsupervised learning algorithm. When we classify a document, we first add special tags to some words in the text, then match the tags within a sentence with some phrase patterns to get the sentiment orientation of the sentence. At last, we add up the sentiment orientation of each sentence. We classify the text according to this summation. The method achieves an accuracy rate of 86% when used to evaluate sports reviews from some Websites.
  • Keywords
    computational linguistics; natural languages; pattern classification; text analysis; unsupervised learning; Web site; document classification; pattern classification; phrase pattern-based method; sentiment classification; tag matching; text sentiment orientation; unsupervised learning; word tags; Computer science; Feedback; Information filtering; Information filters; Information technology; Internet; Natural language processing; Pattern matching; Text categorization; Unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology, 2004. CIT '04. The Fourth International Conference on
  • Print_ISBN
    0-7695-2216-5
  • Type

    conf

  • DOI
    10.1109/CIT.2004.1357349
  • Filename
    1357349