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arXiv cs.CL
arXiv cs.CL
7/10/2026
Unveiling Public Opinion: A Study of Sentiment Analysis Using LSTM and Traditional Models

Unveiling Public Opinion: A Study of Sentiment Analysis Using LSTM and Traditional Models

Short summary

This arXiv paper evaluates sentiment analysis models on Twitter data, finding LSTM networks achieve 90.98% training and 80% testing accuracy. Results demonstrate deep learning outperforms traditional ML—logistic regression, random forest, naive Bayes, gradient boosting—at capturing sequential and contextual patterns in text.

  • •LSTM achieves 90.98% training / 80% testing accuracy on Kaggle Twitter sentiment dataset
  • •Compared against logistic regression, random forest, naive Bayes, and gradient boosting
  • •Deep learning outperforms traditional ML at capturing sequential and contextual text patterns

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Read full article at arXiv cs.CL

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