%0 Journal Article %A Sarah O. Alhumoud and Mawaheb I. Altuwaijri and Tarfa M. Albuhairi and Wejdan M. Alohaideb %D 2015 %J International Journal of Computer and Information Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 97, 2015 %T Survey on Arabic Sentiment Analysis in Twitter %U https://publications.waset.org/pdf/10000687 %V 97 %X Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter. %P 364 - 368