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What is Twitter Sentiment Analysis Techniques about?

This document summarizes a presentation on Twitter sentiment analysis. It discusses how sentiment analysis is used to analyze opinions in text. It also describes some of the challenges in analyzing sentiment in tweets, such as informal language and limited characters. Various preprocessing and modeling techniques are outlined, including removing usernames, links, and stopwords. Results show Naive Bayes, Maximum Entropy, and Support Vector Machine classifiers achieving around 75-77% accuracy on a dataset of

Author

Raj Jha

Language

EN