Research Output
Enhanced SenticNet with affective labels for concept-based opinion mining
  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.

  • Type:

    Article

  • Date:

    21 January 2013

  • Publication Status:

    Published

  • DOI:

    10.1109/MIS.2013.4

  • ISSN:

    1541-1672

  • Funders:

    Historic Funder (pre-Worktribe)

Citation

Poria, S., Gelbukh, A., Hussain, A., Howard, N., Das, D., & Bandyopadhyay, S. (2013). Enhanced SenticNet with affective labels for concept-based opinion mining. IEEE Intelligent Systems, 28(2), 2-9. https://doi.org/10.1109/MIS.2013.4

Authors

Keywords

Data mining, Knowledge discovery, Emotion recognition, Intelligent systems, Vocabulary, Feature extraction, Information analysis, Natural language processing, intelligent systems, SenticNet, sentic computing, sentiment analysis, opinion mining, emotion lexicon, WordNet-Affect

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