This paper introduces MADAD, a general-purpose annotation tool for Arabic text with focus on readability annotation. This tool will help in overcoming the problem of lack of Arabic readability training data by providing an online environment to collect readability assessments on various kinds of corpora. Also the tool supports a broad range of annotation tasks for various linguistic and semantic phenomena by allowing users to create their customized annotation schemes.

Research interest in Arabic sentiment analysis (ASA) is rapidly increasing, therefore it is important to compile, document and analyze efforts in this area to facilitate further development. These ASA efforts aim to create tools that can sift through and gain meaningful knowledge from the unending data explosion. ASA approaches have continued to evolve despite lack in Arabic linguistic resources. In this paper we conduct a comprehensive and up-to-date review of recent resources for ASA.

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