Determining Word-Emotion Associations from Tweets by Multi-label Classification

  title={Determining Word-Emotion Associations from Tweets by Multi-label Classification},
  author={Felipe Bravo-Marquez and Eibe Frank and Saif Mohammad and Bernhard Pfahringer},
  journal={2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI)},
The automatic detection of emotions in Twitter posts is a challenging task due to the informal nature of the language used in this platform. In this paper, we propose a methodology for expanding the NRC word-emotion association lexicon for the language used in Twitter. We perform this expansion using multi-label classification of words and compare different word-level features extracted from unlabelled tweets such as unigrams, Brown clusters, POS tags, and word2vec embeddings. The results show… CONTINUE READING
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