• DocumentCode
    18989
  • Title

    Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining

  • Author

    Poria, S. ; Gelbukh, A. ; Hussain, Amir ; Howard, Newton ; Das, Divya ; Bandyopadhyay, Supriyo

  • Volume
    28
  • Issue
    2
  • fYear
    2013
  • fDate
    March-April 2013
  • Firstpage
    31
  • Lastpage
    38
  • Abstract
    SenticNet 1.0 is one of the most widely used, publicly available resources for concept-based opinion mining. The presented methodology enriches SenticNet concepts with affective information by assigning an emotion label.
  • Keywords
    Internet; data mining; SenticNet 1.0; SenticNet concepts; affective information; affective labels; concept-based opinion mining; emotion label; Data mining; Emotion recognition; Feature extraction; Information analysis; Intelligent systems; Knowledge discovery; Natural language processing; Vocabulary; Data mining; Emotion recognition; Feature extraction; Information analysis; Intelligent systems; Knowledge discovery; Natural language processing; SenticNet; Vocabulary; WordNet-Affect; emotion lexicon; intelligent systems; opinion mining; sentic computing; sentiment analysis;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2013.4
  • Filename
    6415892
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=18989