@InProceedings{diab:2016:VarDial3,
  author    = {Diab, Mona},
  title     = {Processing Dialectal Arabic: Exploiting Variability and Similarity to Overcome Challenges and Discover Opportunities},
  booktitle = {Proceedings of the Third Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial3)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {42},
  abstract  = {We recently witnessed an exponential growth in dialectal Arabic usage in both
	textual data and speech recordings especially in social media. Processing such
	media is of great utility for all kinds of applications ranging from
	information extraction to social media analytics for political and commercial
	purposes to building decision support systems. Compared to other languages,
	Arabic, especially the informal variety, poses a significant challenge to
	natural language processing algorithms since it comprises multiple dialects,
	linguistic code switching, and a lack of standardized orthographies, to top its
	relatively complex morphology. Inherently, the problem of processing Arabic in
	the context of social media is the problem of how to handle resource poor
	languages. In this talk I will go over some of our insights to some of these
	problems and show how there is a silver lining where we can generalize some of
	our solutions to other low resource language contexts.},
  url       = {http://aclweb.org/anthology/W16-4805}
}