Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums
ACM Transactions on Information Systems (TOIS)
Mining Arabic Business Reviews
ICDMW '10 Proceedings of the 2010 IEEE International Conference on Data Mining Workshops
Sentence-Level and Document-Level Sentiment Mining for Arabic Texts
ICDMW '10 Proceedings of the 2010 IEEE International Conference on Data Mining Workshops
A proposed sentiment analysis tool for modern Arabic using human-based computing
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
HICSS '12 Proceedings of the 2012 45th Hawaii International Conference on System Sciences
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With the increasing interest in social media, sentiment Analysis has become a hot topic in the research community. This is due to the important applications that can be derived from analyzing people opinions. Although there are many tools that were designed to extract sentiments, they can be only used for Latin Scripts. This presents the need for giving more interest to Arabic sentiment analysis research. In fact, earlier research in this field is limited and most of them focused on formal Arabic. For that reason, the paper attempts to investigate the problems of analyzing informal Arabic sentiments. To explore these problems, an experiment based on a dictionary look-up process was carried out on Twitter Arabic messages. As a result of this experiment, a classification of the encountered problems is provided. This classification can be considered as a step toward designing efficient sentiment Analysis tools for informal Arabic. In addition, highlighting these problems may encourage researchers to contribute more in this field.