Text Emotion Detection Using Machine Learning And NLP

Authors(5) :-Amal Shameem, Rameshbabu G, Vigneshwaran L, Sundar K, Mrs. K. Veena

In today’s technological world, a majority of users across the world have access to Internet for communication via text, image, audio and video. People from diverse backgrounds exchange information on current scenarios and project their own views on them over social media. There is a need to understand and recognize the behavior of such large text information on people by analyzing their emotions. Emotions play a vital role in human interaction. We recognize emotion of a person from their speech, face gesture, body language and sign actions. Since humans use many text devices to make interactions these days, emotion extraction from the text has drawn a lot of importance. It is therefore crucial that emotions in textual conversation need to be well understood by the machines, which ultimately provide users with emotional awareness feedback. The experimental results proved that Machine learning based text emotion classification provides relatively higher accuracy compared to the existing learning methods.

Authors and Affiliations

Amal Shameem
UG Scholar, Department of Computer Science and Engineering, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India
Rameshbabu G
UG Scholar, Department of Computer Science and Engineering, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India
Vigneshwaran L
UG Scholar, Department of Computer Science and Engineering, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India
Sundar K
UG Scholar, Department of Computer Science and Engineering, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India
Mrs. K. Veena
Assistant Professor, Department of Computer Science and Engineering, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India

Machine Learning, Emotion Detection, NLP, Learning

  1. Jeffrey F. Cohn, and Gary S. Katz. "Bimodal expression of emotion by face and voice." Proceedings of the sixth ACM international conference on Multimedia: Face/gesture recognition and their applications. ACM, 1998.
  2. Zahra Khalili, and Mohammad Hasan Moradi. "Emotion recognition system using brain and peripheral signals: using correlation dimension to improve the results of EEG." Neural Networks, 2009. IJCNN 2009. International Joint Conference on. IEEE, 2009.
  3. Liyanage C. De Silva, and Pei Chi Ng. "Bimodal emotion recognition." Automatic Face and Gesture Recognition, 2000. Proceedings. Fourth IEEE International Conference on. IEEE, 2000.
  4. Torao Yanaru, "An emotion processing system based on fuzzy inference and subjective observations." Artificial Neural Networks and Expert Systems, 1995. Proceedings., Second New Zealand International Two-Stream Conference on. IEEE, 1995.
  5. EC-C. Kao, et al. "Towards Text-based Emotion Detection A Survey and Possible Improvements." Information Management and Engineering, 2009. ICIME'09. International Conference on. IEEE, 2009.
  6. Erik Cambria, Andrew Livingstone, and Amir Hussain. "The hourglass of emotions." Cognitive behavioural systems. Springer Berlin Heidelberg, 2012. 144-157.
  7. P. Ekman, (1999) Basic emotions. In T. Dalgleish and T. Power (Eds.) The handbook of cognition and emotion. Pp. 45-60. New York.: John Wiley & Sons.
  8. Jeffrey T. Hancock , Christopher Landrigan, and Courtney Silver. "Expressing emotion in text-based communication." Proceedings of the SIGCHI conference on Human factors in computing systems. ACM, 2007.
  9. Charles E. Osgood. Cross-cultural universals of affective meaning. University of Illinois Press, 1975.
  10. Charles E. Osgood, and Oliver Tzeng. Language, meaning, and culture: The selected papers of CE Osgood. Praeger Publishers, 1990.
  11. Carlo Strapparava, and Alessandro Valitutti. "WordNet Affect: an Affective Extension of WordNet." LREC. Vol. 4. 2004.
  12. Carlo Strapparava, and Rada Mihalcea. "Learning to identify emotions in text." Proceedings of the 2008 ACM symposium on Applied computing. ACM, 2008.

Publication Details

Published in : Volume 9 | Issue 3 | May-June 2022
Date of Publication : 2022-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 361-365
Manuscript Number : IJSRSET2293145
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Amal Shameem, Rameshbabu G, Vigneshwaran L, Sundar K, Mrs. K. Veena, " Text Emotion Detection Using Machine Learning And NLP, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 3, pp.361-365, May-June-2022. Journal URL : https://res.ijsrset.com/IJSRSET2293145

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