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Reseach Article

Emotion Detection using Lexical Chains

by M. Naveen Kumar, R. Suresh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 57 - Number 4
Year of Publication: 2012
Authors: M. Naveen Kumar, R. Suresh
10.5120/9099-3213

M. Naveen Kumar, R. Suresh . Emotion Detection using Lexical Chains. International Journal of Computer Applications. 57, 4 ( November 2012), 1-4. DOI=10.5120/9099-3213

@article{ 10.5120/9099-3213,
author = { M. Naveen Kumar, R. Suresh },
title = { Emotion Detection using Lexical Chains },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 57 },
number = { 4 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume57/number4/9099-3213/ },
doi = { 10.5120/9099-3213 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:59:32.645373+05:30
%A M. Naveen Kumar
%A R. Suresh
%T Emotion Detection using Lexical Chains
%J International Journal of Computer Applications
%@ 0975-8887
%V 57
%N 4
%P 1-4
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Emotion detection has become an indispensable task in Natural Language Processing (NLP) in recent times. Emotion detection has been done using various knowledge based and corpus based methods. In this paper, we propose a methodology for emotion detection using lexical chains. Lexical chains easily identify the coherent concepts present in the text and so the emotion detection is also done with much ease. We have handled six types of emotions namely happiness, sadness, anger, fear, disgust and surprise. We have evaluated our method with the existing methods and we have shown better performance.

References
  1. Andrea Esuli , Fabrizio Sebastiani. 2006. SENTIWORDNET- A publically available open source for opinion mining In Proceedings of the 5th Conference on Language Resources and Evaluation (LREC'06.
  2. Alastair J. Gill, Darren Gergle, Robert M. French, Jon Oberlander 2008. Emotion Rating from Short Blog Texts. In Proceedings of CHI 2008, April 5–10, 2008, Florence, Italy.
  3. Carlo Strapparava, Rada . 2008. Learning to Identify Emotions in Text. In SAC'08 March 1620, , Fortaleza, Cear´a, Brazil.
  4. Cecilia Ovesdotter Alm, Dan Roth. Richard Sproat. 2005. Emotions from text: machine learning for text-based emotion prediction. In Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing.
  5. Changhua Yang Kevin Hsin-Yih Lin Hsin-Hsi Chen. 2007. Emotion Classification Using WEB Blog Corpora. WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence.
  6. Shenghua Bao, Shengliang Xu, Li Zhang, Rong Yan, Zhong Su, Dingyi Han, and Yong Yu. 2012. Mining Social Emotions from Affective Text. In IEEE Transactions on Knowledge and Data Engineering, VOL. 24, NO. 9, SEPTEMBER 2012
  7. Regina Barzilay and Michael Elhadad. 1997. Using Lexical Chains for Text Summarization. In In Proceedings of the ACL Workshop on Intelligent Scalable Text Summarization
Index Terms

Computer Science
Information Sciences

Keywords

Lexical chains Emotion Detection Sentiment Analysis