@InProceedings{mubarak-darwish-magdy:2017:ALW1,
  author    = {Mubarak, Hamdy  and  Darwish, Kareem  and  Magdy, Walid},
  title     = {Abusive Language Detection on Arabic Social Media},
  booktitle = {Proceedings of the First Workshop on Abusive Language Online},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, BC, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {52--56},
  abstract  = {In this paper, we present our work on detecting
	abusive language on Arabic social
	media. We extract a list of obscene
	words and hashtags using common patterns
	used in offensive and rude communications.
	We also classify Twitter users
	according to whether they use any of these
	words or not in their tweets. We expand
	the list of obscene words using this classification, and we report results on a
	newly created dataset of classified Arabic tweets
	(obscene, offensive, and clean). We make
	this dataset freely available for research, in
	addition to the list of obscene words and
	hashtags. We are also publicly releasing
	a large corpus of classified user comments
	that were deleted from a popular Arabic
	news site due to violations the site’s rules
	and guidelines.},
  url       = {http://www.aclweb.org/anthology/W17-3008}
}