@InProceedings{nozza-fersini-messina:2017:EACLlong,
  author    = {Nozza, Debora  and  Fersini, Elisabetta  and  Messina, Enza},
  title     = {A Multi-View Sentiment Corpus},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {273--280},
  abstract  = {Sentiment Analysis is a broad task that involves the analysis of various aspect
	of the natural language text. However, most of the approaches in the state of
	the art usually  investigate independently each aspect, i.e. Subjectivity
	Classification, Sentiment Polarity Classification, Emotion Recognition, Irony
	Detection. In this paper we present a Multi-View Sentiment Corpus (MVSC), which
	comprises 3000 English microblog posts related the movie domain. Three
	independent annotators manually labelled MVSC, following a broad annotation
	schema about different aspects that can be grasped from natural language text
	coming from social networks. The contribution is therefore a corpus that
	comprises five different views for each message, i.e. subjective/objective,
	sentiment polarity, implicit/explicit, irony, emotion.
	In order to allow a more detailed investigation on the human labelling
	behaviour, we provide the annotations of each  human annotator involved.},
  url       = {http://www.aclweb.org/anthology/E17-1026}
}