Mining Emotion Correlations Through Deep Learning

Authors

  • Jagadish Nimmagadda Department of Computer Applications, Musaliar College of Engineering & Technology, Pathanamthitta, Kerala, India
  • Rujuta Vartak Professor, Department of Computer Applications, Musaliar College of Engineering & Technology, Pathanamthitta, Kerala, India

DOI:

https://doi.org/10.66069/ojspub.16560909

Keywords:

Deep Learning, RoBERTa, LSTM, GUI

Abstract

In this project, we present a hybrid model adopting deep-learning techniques for sentiment categorization and emotion correlation mining using RoBERTa and LSTM. The model applies LSTM architectures to learn and predict sequences and to tokenize and embed contextual words with RoBERTa. The intuitive GUI from the model is claimed to improve classification accuracy.

Downloads

Published

2026-09-26

How to Cite

Nimmagadda, J., & Vartak, R. (2026). Mining Emotion Correlations Through Deep Learning. Journal of Research in Science and Engineering, 8(9), 38–42. https://doi.org/10.66069/ojspub.16560909

Issue

Vol. 8 No. 9 (2026)

Section

Articles

License

Copyright (c) 2026 Jagadish Nimmagadda, Rujuta Vartak

Creative Commons License

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


Deprecated: json_decode(): Passing null to parameter #1 ($json) of type string is deprecated in /www/bryanhousepub/ojs/plugins/generic/citations/CitationsPlugin.inc.php on line 49