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

Other available revisons

Version	Changelog	Date
1.0.1	Initial Announcement on mloss.org.	May 14, 2018, 08:20:50
1.0.0	Initial Announcement on mloss.org.	November 1, 2017, 02:24:58

Comments

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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