%0 Journal Article %A Adel Assiri and Ahmed Emam and Hmood Al-Dossari %D 2016 %J International Journal of Computer and Information Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 110, 2016 %T Saudi Twitter Corpus for Sentiment Analysis %U https://publications.waset.org/pdf/10003483 %V 110 %X 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. %P 272 - 275