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Build a engine to capture current sentiments of people on current affairs like sentiments on NBA championship matches or sentiments on United Airlines incident

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GSav90/Sentiment-Analysis-using-live-stream-Twitter-data-NLP-

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Sentiment-Analysis-using-live-stream-Twitter-data-NLP-

• Used nltk for tokenizing, lemmatizing, stop word removal and pos tagging and feature generation.

• Trained multiple naïve bayes and linear classifiers using scikit-learn and compared their accuracy.

• Combined classifier algorithms by creating a voting system and assigning a confidence value to the final verdict. Storing tweets with confidence>80% to the system

• Plotted sentiment trends captured through live streaming data finding response on current affairs.

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Build a engine to capture current sentiments of people on current affairs like sentiments on NBA championship matches or sentiments on United Airlines incident

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