Mission

Building state of the art automated sentiment analysis and opinion mining for Arabic (OMA).


Project Outcomes

Name Description Publication Downloads Extra
Large Scale Arabic Sentiment Lexicon This is the first publicly available large scale Standard Arabic sentiment lexicon (ArSenL). It is a combination of existing resources of ESWN, Arabic WordNet, and the Standard Arabic Morphological Analyzer (SAMA). [2, 9] Slides/Video Links
Annotated Arabic corpora for Credibility This is a credibility annotated Arabic corpus. [11] Slides/Video Links
Annotated Arabic corpora for Sentiment This is an annotated Arabic Sentiment corpus. Coming Soon Coming Soon Slides/Video Links
General-purpose Large Scale Arabic Corpus This is a large scale Arabic corpus used for general purposes. Coming Soon Coming Soon Slides/Video Links
MLA:
No. Title Authors Venue Download Citation
1 A Multiresolution Approach to Recommender Systems Badaro, G., Hajj, H., Haddad, A., El-Hajj, W., & Shaban, K. B. Proceedings of the 8th Workshop on Social Network Mining and Analysis, ACM
2 A large scale Arabic sentiment lexicon for Arabic opinion mining Badaro, G., Baly, R., Hajj, H., Habash, N., & El-Hajj, W. Arabic Natural Language Processing 2014
3 A novel approach for emotion classification based on fusion of text and speech Houjeij, A., Hamieh, L., Mehdi, N., & Hajj, H. Telecommunications (ICT), 2012 19th International Conference
4 A survey of ground-truth in emotion data annotationConstantine, L., & Hajj, H. Pervasive Computing and Communications Workshops (PERCOM Workshops), 2012 IEEE International Conference
5 A framework for emotion mining from text in online social networks Yassine, M., & Hajj, H. Data Mining Workshops (ICDMW), 2010 IEEE International Conference
6 Machine Reading for Notion-Based Sentiment Mining Hobeica, R., Hajj, H., & El Hajj, W. Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference
7 Sentence-level and document-level sentiment mining for Arabic texts Farra, N., Challita, E., Assi, R. A., & Hajj, H. Data Mining Workshops (ICDMW), 2010 IEEE International Conference
8 Annotating Targets of Opinions in Arabic using Crowdsourcing Farra, N., McKeown, K., & Habash, N. In Arabic Natural Language Processing Workshop 2015
9 A Light Lexicon-based Mobile Application for Sentiment Mining of Arabic Tweets. Badaro, G., Baly, R., Akel, R., Fayad, L., Khairallah, J., Hajj, H., … & Shaban, K. B. In Arabic Natural Language Processing Workshop 2015
10 Deep Learning Models for Sentiment Analysis in Arabic Al Sallab, A. A., Baly, R., Badaro, G., Hajj, H., El Hajj, W., & Shaban, K. B. In Arabic Natural Language Processing Workshop 2015
11 Arabic Corpora for Credibility Analysis Ayman AL Zaatari, Rim El Ballouli, Shady Elbassuoni, Wassim El-Hajj, Hazem Hajj, Khaled Shaban, Nizar Habash, Emad Yehya. Language Resources and Evaluation Conference 2016, 23-28 May 2016, Portorož (Slovenia)
12 A meta-framework for modeling the human reading process in sentiment analysis R. Baly, R. Hobeica, H. Hajj, W. El-Hajj, K. B. Shaban, and A. Al-Sallab ACM Transactions on Information Systems (TOIS), 2016
13 A characterization study of arabic twitter data with a benchmarking for state-of-the-art opinion mining models R. Baly, G. Badaro, G. El-Khoury, R. Moukalled, R. Aoun, H. Hajj, W. El-Hajj, N. Habash, and K. B. Shaban WANLP 2017 (co-located with EACL 2017)
14 A Sentiment Treebank and Morphologically Enriched Recursive Deep Models for Effective Sentiment Analysis in Arabic R. Baly, H. Hajj, N. Habash, W. El-Hajj, and K. B. Shaban, ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), 2017.
15 AROMA: A Recursive Deep Learning Model for Opinion Mining in Arabic as a Low Resource Language A. Al-Sallab, R. Baly, H. Hajj, K. B. Shaban, W. El-Hajj, and G. Badaro ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), 2017

Members

Name Role Title/Affiliation Contact Info
Dr. Hazem El Hajj Lead Principal Investigator Associate Professor, Electrical and Computer Engineering, American University of Beirut
Dr. Khaled
Dr. Khaled Bashir Shaaban Co-lead Principal Investigator Associate Professor, Computer Science and Engineering Department, Qatar University
Dr. Wassim
Dr. Wassim El Hajj Principal Investigator Associate Professor and Chairman of Computer Science, American University of Beirut
Dr. Nizar
Dr. Nizar Habash Principal Investigator Associate Professor of Computer Science, New York University Abu Dhabi (NYUAD)
Dr. Shady
Dr. Shady Elbassuoni Collaborator Assistant Professor of Computer Science at the American University of Beirut
Dr. Kathy
Dr. Kathy McKeown Collaborator Henry and Gertrude Rothschild Professor of Computer Science. Director, Data Science Institute
website link
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Name Role Title/Affiliation Contact Info
Ramy Baly
Ramy Baly Research Assistant PhD Candidate in the Electrical and Computer Engineering Department, American University of Beirut
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Gilbert Badaro Research Assistant PhD Candidate in Electrical and Computer Engineering at the American University of Beirut
Ayman Al Zaatari
Ayman Al Zaatari Research Assistant Graduate Student and Assistant Instructor of Computer Science, American University of Beirut
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Reem El Ballouli Research Assistant Research Assistant at American University of Beirut
Wafa Waheeda Syed
Wafa Waheeda Syed Research Assistant Graduate Student, Computer Science and Engineering Department, Qatar University
Noura Farra Research Assistant PhD student in Computer Science at Columbia University

Press

Article Date Published in Link
Analyzing Arabic Sentiment –
How deep learning could leapfrog Arabic sentiment analysis to the cutting edge.
October 26, 2015 MIT Technology Review
Arab Edition
Read Article

Acknowledgement

This work was made possible by NPRP 6-716-1-138 grant from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.


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