期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2014
卷号：5
期号：10
DOI：10.14569/IJACSA.2014.051005
出版社：Science and Information Society (SAI)
摘要：Most of opinion mining works need lexical resources for opinion which recognize the polarity of words (positive/ negative) regardless their contexts which called prior polarity. The word prior polarity may be changed when it is considered in its contexts, for example, positive words may be used in phrases expressing negative sentiments, or vice versa. In this paper, we aim at generating sentiment Arabic lexical semantic database having the word prior coupled with its contextual polarities and the related phrases. To do that, we study first the prior polarity effects of each word using our Sentiment Arabic Lexical Semantic Database on the sentence-level subjectivity and Support Vector Machine classifier. We then use the seminal English two-step contextual polarity phrase-level recognition approach to enhance word polarities within its contexts. Our results achieve significant improvement over baselines.
