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Textual Affect Sensing for Sociable and Expressive Online Communication

  • Alena Neviarouskaya
  • Helmut Prendinger
  • Mitsuru Ishizuka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4738)

Abstract

In this paper, we address the tasks of recognition and interpretation of affect communicated through text messaging. The evolving nature of language in online conversations is a main issue in affect sensing from this media type, since sentence parsing might fail while syntactical structure analysis. The developed Affect Analysis Model was designed to handle not only correctly written text, but also informal messages written in abbreviated or expressive manner. The proposed rule-based approach processes each sentence in sequential stages, including symbolic cue processing, detection and transformation of abbreviations, sentence parsing, and word/phrase/sentence-level analyses. In a study based on 160 sentences, the system result agrees with at least two out of three human annotators in 70% of the cases. In order to reflect the detected affective information and social behaviour, an avatar was created.

Keywords

Affective sensing from text affective user interface avatar emotions online communication language parsing and understanding text analysis 

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References

  1. 1.
    Allwood, J.: Bodily Communication Dimensions of Expression and Content. In: Multimodality in Language and Speech Systems, pp. 7–26. Kluwer Academic Publishers, Netherlands (2002)Google Scholar
  2. 2.
    Andreevskaia, A., Bergler, S.: Mining WordNet for Fuzzy Sentiment: Sentiment Tag Extraction from WordNet Glosses. In: Proceedings of EACL 2006, Italy (2006)Google Scholar
  3. 3.
    Benamara, F., Cesarano, C., Picariello, A., Reforgiato, D., Subrahmanian, V.: Sentiment Analysis: Adjectives and Adverbs are Better than Adjectives Alone. In: Proceedings of ICWSM 2007, OMNIPRESS, Boulder, Colorado (2007)Google Scholar
  4. 4.
    Biber, D., Johansson, S., Leech, G., Conrad, S., Finegan, E., Quirk, R.: Longman Grammar of Spoken and Written English. Pearson Education Limited (1999)Google Scholar
  5. 5.
    Boucouvalas, A.C.: Real Time Text-to-Emotion Engine for Expressive Internet Communications. In: Being There: Concepts, effects and measurement of user presence in synthetic environments, pp. 306–318. IOS Press, Amsterdam (2003)Google Scholar
  6. 6.
  7. 7.
    Cowie, R., Douglas-Cowie, E., Tsapatsoulis, N., Votsis, G., Kollias, S., Fellenz, W., et al.: Emotion Recognition in Human-Computer Interaction. IEEE Signal Processing Magazine 1, 32–80 (2001)CrossRefGoogle Scholar
  8. 8.
    De Rosis, F., Mazzotta, I., Miceli, M., Poggi, I.: Persuasion Artifices to Promote Wellbeing. In: Proceedings of First International Conference on Persuasive Technology for Human Well-being, Netherlands, pp. 84–95 (2006)Google Scholar
  9. 9.
    Izard, C.E.: Human Emotions. Plenum Press, New York, NY (1977)Google Scholar
  10. 10.
    Kamps, J., Marx, M.: Words with Attitude. In: Proceedings of BNAIC 2002, pp. 449–450 (2002)Google Scholar
  11. 11.
    Kim, S.-M., Hovy, E.: Automatic Detection of Opinion Bearing Words and Sentences. In: Proceedings of IJCNLP 2005 (2005)Google Scholar
  12. 12.
    Leshed, G., Kaye, J.: Understanding How Bloggers Feel: Recognizing Affect in Blog Posts. In: Extended Abstracts of CHI 2006, 1019–1024 (2006)Google Scholar
  13. 13.
    Liu, H., Lieberman, H., Selker, T.: A Model of Textual Affect Sensing using Real-World Knowledge. In: Proceedings of IUI 2003, pp. 125–132 (2003)Google Scholar
  14. 14.
    Mihalcea, R., Liu, H.A: Corpus-based Approach to Finding Happiness. In: Proceedings of the AAAI Spring Symposium on Computational Approaches to Weblogs (2006)Google Scholar
  15. 15.
    Mishne, G.: Experiments with Mood Classification in Blog Posts. In: Proceedings of the First Workshop on Stylistic Analysis of Text for Information Access (2005)Google Scholar
  16. 16.
    Mulder, M., Nijholt, A., den Uyl, M., Terpstra, P.: Lexical Grammatical Implementation of Affect. In: Proceedings of the 7th International Conference on Text, Speech and Dialogue, pp. 171–178. Springer, Heidelberg (2004)Google Scholar
  17. 17.
  18. 18.
    Neviarouskaya, A., Prendinger, H., Ishizuka, M.: Analysis of Affect Expressed through the Evolving Language of Online Communication. In: Proceedings of IUI 2007, pp. 278–281. ACM Press, New York (2007)CrossRefGoogle Scholar
  19. 19.
    Olveres, J., Billinghurst, M., Savage, J., Holden, A.: Intelligent, Expressive Avatars. In: Proceedings of WECC 1998, pp. 47–55 (1998)Google Scholar
  20. 20.
    Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? Sentiment Classification Using Machine Learning Techniques. In: Proceedings of the Conference on Emprirical Methods in Natural Language Processing (2002)Google Scholar
  21. 21.
    Picard, R.: Affective Computing. The MIT Press, Cambridge, MA (1997)Google Scholar
  22. 22.
    Poggi, I., Pelachaud, C.: Performative Faces. Speech Communication 26, 5–21 (1998)CrossRefGoogle Scholar
  23. 23.
    Read, J.: Recognising Affect in Text using Pointwise-Mutual Information. Master thesis, University of Sussex (2004)Google Scholar
  24. 24.
    Rheingold, H.: The Virtual Community: Homesteading on the Electronic Frontier. Wesley Publishing, Menlo Park, CA (1993)Google Scholar
  25. 25.
    Strapparava, C., Valitutti, A., Stock, O.: Dances with Words. In: Proceedings of IJCAI 2007, Hyderabad, India, pp. 1719–1724 (2007)Google Scholar
  26. 26.
    Strapparava, C., Valitutti, A.: WordNet-Affect: an Affective Extension of WordNet. In: Proceedings of LREC 2004, pp. 1083–1086 (2004)Google Scholar
  27. 27.
    Subasic, P., Huettner, A.: Affect Analysis of Text Using Fuzzy Semantic Typing. IEEE Transactions on Fuzzy Systems 9(4), 483–496 (2001)CrossRefGoogle Scholar
  28. 28.
    Turney, P.D.: Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. In: Proceedings of ACL 2002, USA (2002)Google Scholar
  29. 29.
    Weblog Data Collection. BuzzMetrics, Inc., http://www.nielsenbuzzmetrics.com
  30. 30.
    Wilson, T., Wiebe, J., Hoffmann, P.: Recognizing Contextual Polarity in Phrase-level Sentiment Analysis. In: Proceedings of HLT/EMNLP 2005, Vancouver, Canada (2005)Google Scholar
  31. 31.
    Chuang, Z.-J., Wu., C.-H.: Multi-Modal Emotion Recognition from Speech and Text. Computational Linguistic and Chinese Language Processing 9(2), 45–62 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Alena Neviarouskaya
    • 1
  • Helmut Prendinger
    • 2
  • Mitsuru Ishizuka
    • 1
  1. 1.University of Tokyo, Department of Information and Communication EngineeringJapan
  2. 2.National Institute of InformaticsJapan

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