Skip to main content
SpringerLink
Log in

A Learning Based Emotion Classifier with Semantic Text Processing

  • Conference paper
Advances in Intelligent Informatics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 320))

Abstract

In this modern era, we depend more and more on machines for day to day activities. However, there is a huge gap between computer and human in emotional thinking, which is the central factor in human communication. This gap can be bridged by implementing several computational approaches, which induce emotional intelligence into a machine. Emotion detection from text is one such method to make the computers emotionally intelligent because text is one of themajor media for communication among humans and with the computers. In this paper, we propose an approachwhich adds natural language processing techniques to improve the performance of learning based emotion classifier by considering the syntactic and semantic features of text. We also present a comprehensive overview of emerging field of emotion detection from text.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aman, S., Szpakowicz, S.: Using Roget’s thesaurus for fine-grained emotion recognition. In: Proceedings of the Third International Joint Conference on Natural Language Processing, IJCNLP 2008, pp. 296–302 (2008)

    Google Scholar 

  2. Ameeta, A., Aijun, A.: Unsupervised emotion detection from text using semantic and syntactic relations. In: Proceedings of the 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology, WI-IAT 2012, vol. 01, pp. 346–353. IEEE Computer Society, Washington, DC (2012), http://dl.acm.org/citation.cfm?id=2457524.2457613

    Google Scholar 

  3. Bhowmick, P.K., Basu, A., Mitra, P.: Reader Perspective Emotion Analysis in Text through Ensemble based Multi-Label Classification Framework. Computer and Information Science 2(4), 64–74 (2009)

    Article  Google Scholar 

  4. Binali, H., Wu, C., Potdar, V.: Computational approaches for emotion detection in text. In: 2010 4th IEEE International Conference on Digital Ecosystems and Technologies (DEST), pp. 172–177 (2010), doi:10.1109/DEST.2010.5610650

    Google Scholar 

  5. Chaumartin, F.R.: UPAR7: A knowledge-based system for headline sentiment tagging. In: Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), Prague, Czech Republic, pp. 422–425 (2007), http://hal.archives-ouvertes.fr/hal-00611242

  6. Ekman, P.: Basic Emotions. In: Handbook of Cognition and Emotion (1999)

    Google Scholar 

  7. Esuli, A., Sebastiani, F.: SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining. In: 5th Conference on Language Resources and Evaluation, pp. 417–422 (2006), http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.61.7217

  8. Ikonomakis, M., Kotsiantis, S., Tampakas, V.: Text classification using machine learning techniques. WSEAS Transactions on Computers 4(8), 966–974 (2005)

    Google Scholar 

  9. Liu, H., Lieberman, H., Selker, T.: A model of textual affect sensing using real-world knowledge. In: Proceedings of the 8th International Conference on Intelligent User Interfaces, IUI 2003, pp. 125–132. ACM, New York (2003), http://doi.acm.org/10.1145/604045.604067 , doi:10.1145/604045.604067

    Google Scholar 

  10. Hancock, J.T., Landrigan, C., Silver, C.: Expressing emotion in text-based communication. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 929–932. ACM (2007)

    Google Scholar 

  11. Ma, C., Prendinger, H., Ishizuka, M.: Emotion estimation and reasoning based on affective textual interaction. In: Tao, J., Tan, T., Picard, R.W. (eds.) ACII 2005. LNCS, vol. 3784, pp. 622–628. Springer, Heidelberg (2005), doi:10.1007/11573548_80

    Chapter  Google Scholar 

  12. Katz, P., Singleton, M., Wicentowski, R.: Swat-mp: The semeval-2007 systems for task 5 and task 14. In: Proceedings of the 4th International Workshop on Semantic Evaluations, SemEval 2007, pp. 308–313. Association for Computational Linguistics, Stroudsburg (2007), http://dl.acm.org/citation.cfm?id=1621474.1621541

    Google Scholar 

  13. Kozareva, Z., Navarro, B., Vázquez, S., Montoyo, A.: Ua-zbsa: A headline emotion classification through web information. In: Proceedings of the 4th International Workshop on Semantic Evaluations, SemEval 2007, pp. 334–337. Association for Computational Linguistics, Stroudsburg (2007), http://dl.acm.org/citation.cfm?id=1621474.1621546

    Google Scholar 

  14. Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S.J., McClosky, D.: The Stanford CoreNLP natural language processing toolkit. In: Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 55–60 (2014), http://www.aclweb.org/anthology/P/P14/P14-5010

  15. de Marneffe, M.C., MacCartney, B., Manning, C.D.: Generating typed dependency parses from phrase structure trees. In: LREC (2006), http://nlp.stanford.edu/pubs/LREC06_dependencies.pdf

  16. Al Masum, S., Prendinger, H., Ishizuka, M.: Emotion sensitive news agent: An approach towards user centric emotion sensing from the news. In: IEEE/WIC/ACM International Conference on Web Intelligence, pp. 614–620 (2007), doi:10.1109/WI.2007.124

    Google Scholar 

  17. Ortony, A., LClore, G., Collins, A.: The Cognitive Structure of Emotions. Cambridge University Press (1990)

    Google Scholar 

  18. Pennebaker, J., Francis, M., Booth, R.: Linguistic inquiry and word count (computer software). Erlbaum Publishers, Mahwah (2001)

    Google Scholar 

  19. Perikos, I., Hatzilygeroudis, I.: Recognizing emotion presence in natural language sentences. In: Iliadis, L., Papadopoulos, H., Jayne, C. (eds.) EANN 2013, Part II. CCIS, vol. 384, pp. 30–39. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  20. Picard, R.W.: Affective Computing. The MIT Press, Cambridge (1997)

    Google Scholar 

  21. Plutchik, R.: The Emotions. University Press of America, Inc. (1991)

    Google Scholar 

  22. Salovey, P., Brackett, M.A.P., Mayer, J.: Emotional Intelligence: Key Readings on the Mayer and Salovey Model. Natl Professional Resources Inc. (2004)

    Google Scholar 

  23. Scherer, K.R., Wallbott, H.: International survey on emotion antecedents and reactions (isear) (1990), http://www.unige.ch/fapse/emotion/databanks/isear.html

  24. Stone, P.J., Dunphy, D.C., Smith, M.S., Ogilvie, D.M.: The General Inquirer: A Computer Approach to Content Analysis. MIT Press, Cambridge (1966)

    Google Scholar 

  25. Strapparava, C., Mihalcea, R.: Semeval-2007 task 14: Affective text. In: Proceedings of the 4th International Workshop on Semantic Evaluations, SemEval 2007, pp. 70–74. Association for Computational Linguistics, Stroudsburg (2007), http://dl.acm.org/citation.cfm?id=1621474.1621487

    Google Scholar 

  26. Strapparava, C., Mihalcea, R.: Learning to identify emotions in text. In: Proceedings of the 2008 ACM Symposium on Applied Computing, SAC 2008, pp. 1556–1560. ACM, New York (2008), http://doi.acm.org/10.1145/1363686.1364052 , doi:10.1145/1363686.1364052

  27. Strapparava, C., Valitutti, A.: Wordnet-affect: an affective extension of wordnet. In: Proceedings of the 4th International Conference on Language Resources and Evaluation, pp. 1083–1086 (2004)

    Google Scholar 

  28. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann Publishers Inc., San Francisco (2005)

    Google Scholar 

  29. Yang, H., Willis, A., de Roeck, A.: BN A hybrid model for automatic emotion recognition in suicide notes. Biomedical Informatics Insights 5, 17–30 (2012), www.la-press.com/a-hybrid-model-for-automatic-emotion-recognition-in-suicide-notes-article-a3017 , doi:10.4137/BII.S8948

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. MVSR Engineering college, Hyderabad, India

    Vajrapu Anusha & Banda Sandhya

Authors
  1. Vajrapu Anusha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Banda Sandhya
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vajrapu Anusha .

Editor information

Editors and Affiliations

  1. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

  2. Indian Institute of Information Technology and Management- - Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  3. Faculty of Design, Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  4. Department of Information Systems and Operations Management, University of Florida, Warrington College of Business, Florida, Florida, USA

    Selwyn Piramuthu

  5. University of Applied Sciences, Institute for Information Systems, Olten, Switzerland

    Thomas Hanne

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Anusha, V., Sandhya, B. (2015). A Learning Based Emotion Classifier with Semantic Text Processing. In: El-Alfy, ES., Thampi, S., Takagi, H., Piramuthu, S., Hanne, T. (eds) Advances in Intelligent Informatics. Advances in Intelligent Systems and Computing, vol 320. Springer, Cham. https://doi.org/10.1007/978-3-319-11218-3_34

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-11218-3_34

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11217-6

  • Online ISBN: 978-3-319-11218-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation