期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2016
卷号：8
期号：2
页码：17
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Product reviews are becoming increasingly useful. In this paper, Twitter has been chosen as a platform foropinion mining in trading strategy with Mubasher products, which is a leading stock analysis softwareprovider in the Gulf region. This experiment proposes a model for sentiment analysis of Saudi Arabic(standard and Arabian Gulf dialect) tweets to extract feedback from Mubasher products. A hybrid ofnatural language processing and machine learning approaches on building models are used to classifytweets according to their sentiment polarity into one of the classes positive, negative and neutral. Inaddition, Regarding to the comparison between SVM and Bayesian method, we have split the data into twoindependents subsets form different periods and the experiments were carried out for each subsetsrespectively in order to distinction between positive and negative examples by using neutral trainingexamples in learning facilitates. Similar result has been given.
