SenticSpace: Visualizing Opinions and Sentiments in a Multi-dimensional Vector Space

  • Erik Cambria
  • Amir Hussain
  • Catherine Havasi
  • Chris Eckl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6279)


In a world in which millions of people express their feelings and opinions about any issue in blogs, wikis, fora, chats and social networks, the distillation of knowledge from this huge amount of unstructured information is a challenging task. In this work we build a knowledge base which merges common sense and affective knowledge and visualize it in a multi-dimensional vector space, which we call SenticSpace. In particular we blend ConceptNet and WordNet-Affect and use dimensionality reduction on the resulting knowledge base to build a 24-dimensional vector space in which different vectors represent different ways of making binary distinctions among concepts and sentiments.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Erik Cambria
    • 1
  • Amir Hussain
    • 1
  • Catherine Havasi
    • 2
  • Chris Eckl
    • 3
  1. 1.Dept. of Computing Science and MathsUniversity of StirlingScotland, UK
  2. 2.MIT Media LabMITUSA
  3. 3.Sitekit Labs, Sitekit Solutions LtdScotland, UK

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