@InProceedings{canales-EtAl:2017:RANLP,
  author    = {Canales, Lea  and  Daelemans, Walter  and  Boldrini, Ester  and  Martinez-Barco, Patricio},
  title     = {Towards the Improvement of Automatic Emotion Pre-annotation with Polarity and Subjective Information},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {157--163},
  abstract  = {Emotion detection has a high potential positive impact on the benefit of
	business, society, politics or education. Given this, the main objective of our
	research is to contribute to the resolution of one of the most important
	challenges in textual emotion detection: emotional corpora annotation. This
	will be tackled by proposing a semi-automatic methodology. It consists in two
	main phases: (1) an automatic process to pre-annotate the unlabelled sentences
	with a reduced number of emotional categories; and (2) a manual process of
	refinement where human annotators will determine which is the dominant emotion
	between the pre-defined set. Our objective in this paper is to show the
	pre-annotation process, as well as to evaluate the usability of subjective and
	polarity information in this process. The evaluation performed confirms clearly
	the benefits of employing the polarity and subjective information on emotion
	detection and thus endorses the relevance of our approach.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_022}
}