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iWAN NLP Tools
Arabic NLP Tools developed by iWAN Research Group


Arabic is an important language in the Middle East and North Africa where it is the language of trade and academia. Furthermore, Arabic is also the language of Islamic heritage and liturgy, such as the Qur’an, and thus of significance to all Muslims around the world.

However, Arabic has received little attention in computational linguistics. So, this website will try to remedy this shortcoming by showcasing our developed tools and techniques that deliver state-of-the-art applications in a variety of Arabic language processing tasks.



Prof. Hend S. Al-Khalifa

Dr. Maha M. Al-Yahya

Dr. Muna S. Al-Razgan

Dr. Nora S. Al-Twairesh

Ms. Abeer A. Al-Dayel


Papers produced as a result of the above SOFTWARE projects:

[1] Siham AlOtaibi, Maha Al-Yahya, Hend A-Khalifa, Sinaa Alageel, and Nora Abanmy. Readability of Arabic Medicine Information Leaflets: A Machine Learning Approach. Symposium on Data Mining Applications , SDMA2016, 30 March 2016, Riyadh, Saudi Arabia.

[2] Nora Al-Twairesh, Abeer Al-Dayel, Hend Al-Khalifa, Maha Al-Yahya, Sinaa Alageel, and Nora Abanmy. MADAD: A Readability Annotation Tool for Arabic Text. 10th International Conference on Language Resources and Evaluation. 23-28 May 2016, Portorož, Slovenia.

[3] Nora Al-Twairesh, Hend Suliman Al-Khalifa, Abdulmalik Alsalman. AraSenTi: Large-Scale Twitter-Specific Arabic Sentiment Lexicons. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pages 697–705, Berlin, Germany, August 7-12, 2016..


AraSenti/AraSentiLexicon V1.0 (download)