%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