The study presents a comprehensive comparison for Sentimental Analysis between three selected machine learning algorithms-Random Forest, Support Vector Machine (SVM), and Convolutional Neural Network (CNN). Using a dataset obtained from Kaggle which is a twitter-based datasets and labeled with different sentiments and the tweets. This paper aims to identify the most effective model on the basis of key metrics such as accuracy, precision, recall and F1 Score. After implementation, SVM model resulted to be most effective than the others with an accuracy rate of 72.15%. © 2026 Institute of Physics Publishing. All rights reserved.

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