Machine learning algorithms analyse textual data's emotional tone in sentiment analysis, a growing area. Deep learning models like CNN, LSTM, and RNN can detect and display complex data associations, making them popular among machine learning algorithms. This study evaluates deep learning models for sentiment analysis.The review examined many research papers to determine each model's pros and cons. The task's requirements, such as text length, computing effectiveness, and linguistic qualities, determine the model used. CNN models worked well for tweets, whereas LSTM models were better for movie reviews. When computing efficiency was important, Recurrent Neural Network (RNN) models were feasible.

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