@article{(Open Science Index):https://publications.waset.org/pdf/10003483,
	  title     = {Saudi Twitter Corpus for Sentiment Analysis},
	  author    = {Adel Assiri and  Ahmed Emam and  Hmood Al-Dossari},
	  country	= {},
	  institution	= {},
	  abstract     = {Sentiment analysis (SA) has received growing
attention in Arabic language research. However, few studies have yet
to directly apply SA to Arabic due to lack of a publicly available
dataset for this language. This paper partially bridges this gap due to
its focus on one of the Arabic dialects which is the Saudi dialect. This
paper presents annotated data set of 4700 for Saudi dialect sentiment
analysis with (K= 0.807). Our next work is to extend this corpus and
creation a large-scale lexicon for Saudi dialect from the corpus.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {10},
	  number    = {2},
	  year      = {2016},
	  pages     = {272 - 275},
	  ee        = {https://publications.waset.org/pdf/10003483},
	  url   	= {https://publications.waset.org/vol/110},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 110, 2016},
	}