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Reseach Article

Emotion Extraction: Machine Learning for Text-based Emotion

Published on May 2012 by Swati D. Bhutekar, Manoj. B. Chandak, A. J. Agrawal
National Conference on Recent Trends in Computing
Foundation of Computer Science USA
NCRTC - Number 1
May 2012
Authors: Swati D. Bhutekar, Manoj. B. Chandak, A. J. Agrawal
8608fa10-48d6-4564-a47a-56fa63ccc2b4

Swati D. Bhutekar, Manoj. B. Chandak, A. J. Agrawal . Emotion Extraction: Machine Learning for Text-based Emotion. National Conference on Recent Trends in Computing. NCRTC, 1 (May 2012), 20-23.

@article{
author = { Swati D. Bhutekar, Manoj. B. Chandak, A. J. Agrawal },
title = { Emotion Extraction: Machine Learning for Text-based Emotion },
journal = { National Conference on Recent Trends in Computing },
issue_date = { May 2012 },
volume = { NCRTC },
number = { 1 },
month = { May },
year = { 2012 },
issn = 0975-8887,
pages = { 20-23 },
numpages = 4,
url = { /proceedings/ncrtc/number1/6515-1005/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Recent Trends in Computing
%A Swati D. Bhutekar
%A Manoj. B. Chandak
%A A. J. Agrawal
%T Emotion Extraction: Machine Learning for Text-based Emotion
%J National Conference on Recent Trends in Computing
%@ 0975-8887
%V NCRTC
%N 1
%P 20-23
%D 2012
%I International Journal of Computer Applications
Abstract

This paper presents an machine learning approach as classification concept will be needed to emotion recognition from textual content. This paper also focuses on Emotion engine available, Corpus needed , textual emotion recognition module etc. In text analysis, all emotional keywords and emotion modification words are manually defined. The emotion intensity levels of emotional keywords and emotion modification words are estimated based on a collected emotion corpus. The final emotional state is determined based on the emotion outputs from the acoustic and textual analyses.

References
  1. Xu Zhe, David John and Anthony C. Boucouvalas, " Text-to-Emotion Engine: Tests of User preferences" Multimedia Communications Research Group, Bournemouth University,
  2. Ricardo A. Calix, Sri Abhishikth Mallepudi, Bin Chen, and Gerald M. Knapp, "Emotion Recognition in Text for 3-D Facial Expression Rendering," IEEE Transactions on Multimedia, vol. 12, no. 6, Oct. 2010, pp- 544
  3. Fazel Keshtkar, Diana Inkpen," A Corpus-based Method for Extracting Paraphrases of Emotion Terms", Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, pages 35–44,Los Angeles, California, June 2010. Association for Computational Linguistics
  4. Curry Guinn and Rob Hubal," Extracting Emotional Information from the Text of Spoken Dialog", RTI International, 3040 Cornwallis Road, Research Triangle Park, North Carolina, USA, 27709
  5. Ze-Jing Chuang and Chung-Hsien Wu," Multi-Modal Emotion Recognition from Speech and Text", Computational Linguistics and Chinese Language Processing Vol. 9, No. 2 , August 2004, pp. 45-62 45 , The Association for Computational Linguistics and Chinese Language Processing
  6. Xu Zhe, David John and Anthony C. Boucouvalas," Emotion Extraction Engine: Expressive Image generator", Multimedia Communications Research Group, School of Design, engineering and Computing, Bournemouth University,
  7. Bassili, J. N. , 1979. Emotion recognition: The role of facial movement and the relative importance of upper and lower areas of the face. Journal of Personality and Social Psychology, 37, pp 2049-2058.
  8. Buck, R. , 2001. Emotional Expression, Communication, and Competence: Applications of a Developmental-Interactionist Theory of Biological, Social, Cognitive and Moral Emotions. University of Connecticut. http://wattlab. coms. uconn. edu/ftp/users/rbuck/Germany01/
  9. Zhe, X. & Boucouvalas, A. C. , 2002. Text-to-Emotion Engine for Real Time Internet Communication. International symposium on Communication Systems, Networks and DSPs, 15-17 July 2002, Staffordshire University,UK, pp 164-168
Index Terms

Computer Science
Information Sciences

Keywords

Emotion Machine Learning Cognitive Styles