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)

Abstract

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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Elliott, C.: The Affective Reasoner: A Process Model of Emotions in a Multi-Agent System. The Institute for the Learning Sciences, Technical Report No. 32 (1992)Google Scholar
  2. 2.
    Ortony, A., Clore, G., Collins, A.: The Cognitive Structure of Emotions. Cambridge University Press, New York (1988)Google Scholar
  3. 3.
    Wiebe, J., Wilson, T., Cardie, C.: Annotating Expressions of Opinions and Emotions in Language. Language Resources and Evaluation 2(3), 165–210 (2005)CrossRefGoogle Scholar
  4. 4.
    Somasundaran, S., Wiebe, J., Ruppenhofer, J.: Discourse Level Opinion Interpretation. In: COLING, Manchester (2008)Google Scholar
  5. 5.
    Wilson, T., Wiebe, J., Hoffmann, P.: Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. In: HLT-EMNLP, Vancouver (2005)Google Scholar
  6. 6.
    Hu, M., Liu, B.: Mining Opinion Features in Customer Reviews. In: AAAI, San Jose (2004)Google Scholar
  7. 7.
    Goertzel, B., Silverman, K., Hartley, C., Bugaj, S., Ross, M.: The Baby Webmind Project. In: AISB, Birmingham (2000)Google Scholar
  8. 8.
    Dyer, M.: Emotions and Their Computations: Three Computer Models. Cognition and Emotion 1(3), 323–347 (1987)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Cambria, E., Hussain, A., Havasi, C., Eckl, C.: Sentic Computing: Exploitation of Common Sense for the Development of Emotion-Sensitive Systems. In: Esposito, A., Campbell, N., Vogel, C., Hussain, A., Nijholt, A. (eds.) Development of Multimodal Interfaces: Active Listening and Synchrony. LNCS, vol. 5967, pp. 148–156. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  10. 10.
    Cambria, E., Hussain, A., Havasi, C., Eckl, C.: Common Sense Computing: From the Society of Mind to Digital Intuition and Beyond. In: Fierrez, J., Ortega-Garcia, J., Esposito, A., Drygajlo, A., Faundez-Zanuy, M. (eds.) Biometric ID Management and Multimodal Communication. LNCS, vol. 5707, pp. 252–259. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  11. 11.
    Havasi, C., Speer, R., Alonso, J.: ConceptNet 3: a Flexible, Multilingual Semantic Network for Common Sense Knowledge. In: RANLP, Borovets (2007)Google Scholar
  12. 12.
    Strapparava, C., Valitutti, A.: WordNet-Affect: an Affective Extension of WordNet. In: LREC, Lisbon (2004)Google Scholar
  13. 13.
    Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)MATHGoogle Scholar
  14. 14.
    Havasi, C., Speer, R., Pustejovsky, J., Lieberman, H.: Digital Intuition: Applying Common Sense Using Dimensionality Reduction. IEEE Intelligent Systems 24(4), 24–35 (2009)CrossRefGoogle Scholar
  15. 15.
    Plutchik, R.: The Nature of Emotions. American Scientist 89(4), 344–350 (2001)Google Scholar
  16. 16.
    Minsky, M.: The Emotion Machine. Simon and Schuster, New York (2006)Google Scholar
  17. 17.
    Wall, M., Rechtsteiner, A., Rocha, L.: Singular Value Decomposition and Principal Component Analysis. In: Berrar, D., et al. (eds.) A Practical Approach to Microarray Data Analysis, pp. 91–109. Kluwer, Norwell (2003)CrossRefGoogle Scholar
  18. 18.
    Eckart, C., Young, G.: The Approximation of One Matrix by Another of Lower Rank. Psychometrika 1(3), 211–218 (1936)CrossRefGoogle Scholar

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

Personalised recommendations