Nora Al-Twairesh


AraSenTi: Large-Scale Twitter-Specific Arabic Sentiment Lexicons
Nora Al-Twairesh | Hend Al-Khalifa | Abdulmalik Al-Salman
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

MADAD: A Readability Annotation Tool for Arabic Text
Nora Al-Twairesh | Abeer Al-Dayel | Hend Al-Khalifa | Maha Al-Yahya | Sinaa Alageel | Nora Abanmy | Nouf Al-Shenaifi
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

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. MADAD is a web-based tool, accessible through any web browser; the main features that distinguish MADAD are its flexibility, portability, customizability and its bilingual interface (Arabic/English).