EmoTxt: A toolkit for emotion recognition from text

We present EmoTxt, a toolkit for emotion recognition from text, trained and tested on a gold standard of about 9K question, answers, and comments from online interactions. We provide empirical evidence of the performance of EmoTxt. To the best of our knowledge, EmoTxt is the first open-source toolkit supporting both emotion recognition from text and training of custom emotion classification models.

[1]  Walter Daelemans,et al.  Pattern for Python , 2012, J. Mach. Learn. Res..

[2]  R. Plutchik.  Emotions : a general psychoevolutionary theory , 1984 .

[3]  Thorsten Joachims,et al.  Training linear SVMs in linear time , 2006, KDD '06.

[4]  Mike Thelwall,et al.  Sentiment strength detection for the social web , 2012, J. Assoc. Inf. Sci. Technol..

[5]  Carlo Strapparava,et al.  WordNet Affect: an Affective Extension of WordNet , 2004, LREC.

[6]  P. Shaver,et al.  Emotion knowledge: further exploration of a prototype approach. , 1987, Journal of personality and social psychology.

[7]  Chih-Jen Lin,et al.  LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..

[8]  Malvina Nissim,et al.  Sentiment Analysis of Microblogging Data , 2018, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

[9]  Jure Leskovec,et al.  A computational approach to politeness with application to social factors , 2013, ACL.

[10]  Shane McIntosh,et al.  Automated Parameter Optimization of Classification Techniques for Defect Prediction Models , 2016, 2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE).

[11]  Nicole Novielli,et al.  Anger and Its Direction in Collaborative Software Development , 2017, 2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER).

[12]  Michele Marchesi,et al.  Are Bullies More Productive? Empirical Study of Affectiveness vs. Issue Fixing Time , 2015, 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories.

[13]  Max Kuhn,et al.  caret: Classification and Regression Training , 2015 .