@InProceedings{pool-nissim:2016:PEOPLES,
  author    = {Pool, Chris  and  Nissim, Malvina},
  title     = {Distant supervision for emotion detection using Facebook reactions},
  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     = {30--39},
  abstract  = {We exploit the Facebook reaction feature in a distant supervised fashion to
	train a support vector machine classifier for emotion detection, using several
	feature combinations and combining different Facebook pages. We test our models
	on existing benchmarks for emotion detection and show that employing only
	information that is derived completely automatically, thus without relying on
	any handcrafted lexicon as it's usually done, we can achieve competitive
	results. The results also show that there is large room for improvement,
	especially by gearing the collection of Facebook pages, with a view to the
	target domain.},
  url       = {http://aclweb.org/anthology/W16-4304}
}