Segmentation of Neural Text and Its Application to Sentiment Analysis

Authors

  • R. Hendra Kumar  KMM Institute of Technology and Sciences, Andhra Pradesh, India
  • C. Kusuma Latha  KMM Institute of Technology and Sciences, Andhra Pradesh, India

Keywords:

Deep learning, Emotion recognition, Bi-LSTM, CNN, Formal text, Emotional states.

Abstract

Poetry and formal texts have gotten less attention in recent years from experts in artificial intelligence than informal textual content such as SMS, email, chat, and online user reviews. Using Deep Learning, this study proposes a text-based emotional state categorization system. The text corpus is used to construct an attention-based Bi-LSTM model and CNN, further which are compared for their accuracy. There are a number of distinct emotional states that which can be classified from the text using the suggested method. These states include neutral, joy, fear, sadness.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2022-12-30

Issue

Volume 8, Issue 6, November-December-2022

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
R. Hendra Kumar, C. Kusuma Latha, " Segmentation of Neural Text and Its Application to Sentiment Analysis" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 6, pp.125-130, November-December-2022.