Shypd.aiThe largest open index of AI toolsSentiment-Analysis-Twitter is an open-source research project for sentiment analysis of Twitter data. It allows researchers to experiment with different feature sets and machine learning classifiers.
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Sentiment-Analysis-Twitter is an open-source research project focused on determining the best combination of feature sets and machine learning classifiers for sentiment analysis of Twitter data. The project explores various pre-processing steps, including handling punctuations, emoticons, Twitter-specific terms, and stemming. It investigates features such as unigrams, bigrams, trigrams, and negation detection, and trains classifiers using algorithms like Naive Bayes, Decision Trees, and Maximum Entropy. The methodology uses a modularized approach, separating feature extraction and classification, which allows for flexible experimentation. While the original project code remains publicly hosted, the project has been sold and is also available as a commercial API through OnePanel Inc.
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