@InProceedings{farra-mckeown:2017:EACLlong,
  author    = {Farra, Noura  and  McKeown, Kathy},
  title     = {SMARTies: Sentiment Models for Arabic Target entities},
  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     = {1002--1013},
  abstract  = {We consider entity-level sentiment analysis in Arabic, a morphologically rich
	language with increasing resources. We present a system that is applied to
	complex posts written in response to Arabic newspaper articles.  Our goal is to
	identify important entity "targets" within the post along with the polarity
	expressed about each target. We achieve significant improvements over multiple
	baselines, demonstrating that the use of specific morphological representations
	improves the performance of identifying both important targets and their
	sentiment, and that the use of distributional semantic clusters further boosts
	performances for these representations, especially when richer linguistic
	resources are not available.},
  url       = {http://www.aclweb.org/anthology/E17-1094}
}