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In the ever-expanding realm of the internet, where vast amounts of data are generated daily, platforms like Twitter become hubs for expressing opinions.This survey delves into sentiment analysis on Twitter, focusing on the challenges posed by unstructured, diverse opinions.Leveraging natural language processing (NLP) techniques, a robust sentiment analysis framework is constructed.The framework utilizes machine learning algorithms such as Naive Bayes, Maximum Entropy, and Support Vector Machine (SVM).A diverse dataset is collected, preprocessed, and used to train and evaluate the model.
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