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- Description:
AffectiveTweets is a WEKA package for analyzing emotion and sentiment of tweets.
The package implements WEKA filters for calculating state-of-the-art affective analysis features from tweets that can be fed into machine learning algorithms. It also implements methods for building affective lexicons and distant supervision methods for training affective models from unlabeled tweets.
- Changes to previous version:
Initial Announcement on mloss.org.
- BibTeX Entry: Download
- Supported Operating Systems: Linux, Macosx, Windows
- Data Formats: Arff
- Tags: Affective Computing, Sentiment Analysis, Twitter
- Archive: download here
Comments
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- Felipe Bravo (on May 16, 2018, 01:12:21)
- * Added support for stemming and handling stop words. * Added support for using different tokenizers. * Added new distant supervision filters. * Added new filters for creating affective lexicons.
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