New opportunities and challenges arise with the growing availability of online Arabic reviews. Sentiment analysis of these reviews can help the beneficiary by summarizing the opinions of others about entities or events. Also, for opinions to be comprehensive, analysis should be provided for each aspect or feature of the entity. In this paper, we propose a generic approach that extracts the entity aspects and their attitudes for reviews written in modern standard Arabic. The proposed approach does not exploit predefined sets of features, nor domain ontology hierarchy. Instead we add sentiment tags on the patterns and roots of an Arabic lexicon and used these tags to extract the opinion bearing words and their polarities. The proposed system is evaluated on the entity-level using two datasets of 500 movie reviews with accuracy 96% and 1000 restaurant reviews with accuracy 86.7%. Then the system is evaluated on the aspect-level using 500 Arabic reviews in different domains (Novels, Products, Movies, Football game events and Hotels). It extracted aspects, at 80.8% recall and 77.5% precision with respect to the aspects defined by domain experts. |
