Bravo-Marquez, F., Frank, E., Pfahringer, B., & Mohammad, S. M. (2019). AffectiveTweets: a Weka package for analyzing affect in tweets. Journal of Machine Learning Research, 20, 1–6.
Permanent Research Commons link: https://hdl.handle.net/10289/12617
AffectiveTweets is a set of programs for analyzing emotion and sentiment of social media messages such as tweets. It is implemented as a package for the Weka machine learning workbench and provides methods for calculating state-of-the-art affect analysis features from tweets that can be fed into machine learning algorithms implemented in Weka. It also implements methods for building affective lexicons and distant supervision methods for training affective models from unlabeled tweets. The package was used by several teams in the shared tasks: EmoInt 2017 and Affect in Tweets SemEval 2018 Task 1.
© 2019 Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer, and Saif M. Mohammad. License: CC-BY 4.0, see https://creativecommons.org/licenses/by/4.0/. Attribution requirements are provided at http://jmlr.org/papers/v20/18-450.html.