Research Output
Affective common sense knowledge acquisition for sentiment analysis
  Thanks to the advent of Web 2.0, the potential for opinion sharing today is unmatched in history. Making meaning out of the hugeamount of unstructured information available online, however, is extremely difficult as web-contents, despite being perfectly suitable forhuman consumption, still remain hardly accessible to machines. To bridge the cognitive and affective gap between word-level naturallanguage data and the concept-level sentiments conveyed by them, affective common sense knowledge is needed. In sentic computing,the general common sense knowledge contained in ConceptNet is usually exploited to spread affective information from selected affectseeds to other concepts. In this work, besides exploiting the emotional content of the Open Mind corpus, we also collect new affectivecommon sense knowledge through label sequential rules, crowd sourcing, and games-with-a-purpose techniques. In particular, wedevelop Open Mind Common Sentics, an emotion-sensitive IUI that serves both as a platform for affective common sense acquisitionand as a publicly available NLP tool for extracting the cognitive and affective information associated with short texts.

  • Date:

    31 December 2012

  • Publication Status:


  • Funders:

    Historic Funder (pre-Worktribe)


Cambria, E., Xia, Y., & Hussain, A. (2012). Affective common sense knowledge acquisition for sentiment analysis



knowledge acquisition, crowd sourcing, games with a purpose, natural language processing, sentic computing

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