@InProceedings{canales-EtAl:2016:PEOPLES,
  author    = {Canales, Lea  and  Strapparava, Carlo  and  Boldrini, Ester  and  Martinez-Barco, Patricio},
  title     = {Innovative Semi-Automatic Methodology to Annotate Emotional Corpora},
  booktitle = {Proceedings of the Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media (PEOPLES)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {91--100},
  abstract  = {Detecting depression or personality traits, tutoring and student behaviour
	systems, or identifying cases of cyber-bulling are a few of the wide range of
	the applications, in which the automatic detection of emotion is a crucial
	element. Emotion detection has the potential of high impact by contributing the
	benefit of business, society, politics or education. Given this context, the
	main objective of our research is to contribute to the resolution of one of the
	most important challenges in textual emotion detection task: the problems of
	emotional corpora annotation. This will be tackled by proposing of a new
	semi-automatic methodology. Our innovative methodology 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 refinement manual process
	where human annotators will determine which is the predominant emotion between
	the emotional categories selected in the phase 1. Our proposal in this paper is
	to show and evaluate the pre-annotation process to analyse the feasibility and
	the benefits by the methodology proposed. The results obtained are promising
	and allow obtaining a substantial improvement of annotation time and cost and
	confirm the usefulness of our pre-annotation process to improve the annotation
	task.},
  url       = {http://aclweb.org/anthology/W16-4310}
}