Emotion Recognition from Text using LSTM algorithm

Authors

  • V Preethi Usha Mittal Institute of Technology, SNDT Women's University, Mumbai, India
  • Nimisha Jadav Usha Mittal Institute of Technology, SNDT Women's University, Mumbai, India
  • Komal Shirsat Usha Mittal Institute of Technology, SNDT Women's University, Mumbai, India
  • Mohan Bonde Usha Mittal Institute of Technology, SNDT Women's University, Mumbai, India

DOI:

https://doi.org/10.26438/ijcse/v8i6.3033

Keywords:

LSTM, Emotion Recognition

Abstract

The growth of social networking sites lead to increase in number of users and the amount of time spent by the users on these sites. In this era of internet, human expresses their emotions, sentiments and feelings via text, comments or tweets. People share their thoughts, feelings, experiences and opinions according to their observation and understanding. Emotion is an appearance of human behavior and plays an important role in human computer interaction. To extract the emotion behind this textual data we have proposed a model, emotion recognition from text. Our method detects emotion from a text-input by using deep learning algorithm Long Short Term Memory (LSTM). Emotions such as anger, love, surprise, joy, sadness and fear are classified through this model and the accuracy of each classifier is calculated.

References

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Published

2020-06-30
CITATION
DOI: 10.26438/ijcse/v8i6.3033
Published: 2020-06-30

How to Cite

[1]
V. Preethi, N. Jadav, K. Shirsat, and M. Bonde, “Emotion Recognition from Text using LSTM algorithm”, Int. J. Comp. Sci. Eng., vol. 8, no. 6, pp. 30–33, Jun. 2020.

Issue

Vol. 8 No. 6 (2020): IJCSE June Edition

Section

Research Article

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