Building state of the art automated sentiment analysis and opinion mining for Arabic (OMA).
| 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 |
| 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 annotation | Constantine, 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 | MLA: | |
| 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 |
 |
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 Bashir Shaaban | Co-lead Principal Investigator | Associate Professor, Computer Science and Engineering Department, Qatar University | |
 |
Dr. Wassim El Hajj | Principal Investigator | Associate Professor and Chairman of Computer Science, American University of Beirut | |
 |
Dr. Nizar Habash | Principal Investigator | Associate Professor of Computer Science, New York University Abu Dhabi (NYUAD) | |
 |
Dr. Shady Elbassuoni | Collaborator | Assistant Professor of Computer Science at the American University of Beirut | |
 |
Dr. Kathy McKeown | Collaborator | Henry and Gertrude Rothschild Professor of Computer Science. Director, Data Science Institute |
|
Name | Role | Title/Affiliation | Contact Info |
|---|---|---|---|---|
 |
Ramy Baly | Research Assistant | PhD Candidate in the Electrical and Computer Engineering Department, American University of Beirut | |
 |
Gilbert Badaro | Research Assistant | PhD Candidate in Electrical and Computer Engineering at the American University of Beirut | |
 |
Ayman Al Zaatari | Research Assistant | Graduate Student and Assistant Instructor of Computer Science, American University of Beirut | |
 |
Reem El Ballouli | Research Assistant | Research Assistant at American University of Beirut | |
 |
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 |
| 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 |
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.
