• DocumentCode
    3301514
  • Title

    Advanced emotion categorization and tagging

  • Author

    Jiang, Peilin ; Ren, Fuji ; Zheng, Nanning

  • Author_Institution
    Fac. of Eng., Univ. of Tokushima, Tokushima
  • fYear
    2008
  • fDate
    19-22 Oct. 2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Affective computing is attracting attentions as a popular growing field with many applications such as Kansei engineering, information retrieval and HCI. But until now the study of fine-grained theory of emotion is still a challenge. In this paper, a novel method to analyze emotion category is proposed according to the statistics of affective property in Dictionary of contemporary Chinese. These emotion categories are called complex emotion. Firstly, over 3,700 common affective words and their detailed explanations had been collected for an affective lexicon, then we analyze the consistent relationship in the affective lexicon and consequently 52 salient complex emotion states are categorized and tagged by a straightforward clustering algorithm. The complex emotions are compared to the traditional definitions of basic emotions in psychology and have been evaluated to be valid in the experiment. Moreover we also have tagged the semantic orientation for the collected words.
  • Keywords
    emotion recognition; natural language processing; pattern classification; advanced emotion categorization; advanced emotion tagging; contemporary Chinese dictionary; emotion category; straightforward clustering algorithm; Artificial intelligence; Human computer interaction; Information retrieval; Natural languages; Psychology; Robots; Speech analysis; Statistical analysis; Tagging; Telecommunication computing; Complex emotion; affective clustering; affective word lexicon; emotion category;
  • 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.2008.4906814
  • Filename
    4906814