@InProceedings{ohman-honkela-tiedemann:2016:PEOPLES,
  author    = {\"{O}hman, Emily  and  Honkela, Timo  and  Tiedemann, J\"{o}rg},
  title     = {The Challenges of Multi-dimensional Sentiment Analysis Across Languages},
  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     = {138--142},
  abstract  = {This paper outlines a pilot study on multi-dimensional and multilingual
	sentiment analysis of social media content. We use parallel corpora of movie
	subtitles as a proxy for colloquial language in social media channels and a
	multilingual emotion lexicon for fine-grained sentiment analyses. Parallel data
	sets make it possible to study the preservation of sentiments and emotions in
	translation and our assessment reveals that the lexical approach shows great
	inter-language agreement. However, our manual evaluation also suggests that the
	use of purely lexical methods is limited and further studies are necessary to
	pinpoint the cross-lingual differences and to develop better sentiment
	classifiers.},
  url       = {http://aclweb.org/anthology/W16-4315}
}