Mazajak: An Online Arabic Sentiment Analyser

Ibrahim Abu Farha, Walid Magdy


Abstract
Sentiment analysis (SA) is one of the most useful natural language processing applications. Literature is flooding with many papers and systems addressing this task, but most of the work is focused on English. In this paper, we present “Mazajak”, an online system for Arabic SA. The system is based on a deep learning model, which achieves state-of-the-art results on many Arabic dialect datasets including SemEval 2017 and ASTD. The availability of such system should assist various applications and research that rely on sentiment analysis as a tool.
Anthology ID:
W19-4621
Volume:
Proceedings of the Fourth Arabic Natural Language Processing Workshop
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Wassim El-Hajj, Lamia Hadrich Belguith, Fethi Bougares, Walid Magdy, Imed Zitouni, Nadi Tomeh, Mahmoud El-Haj, Wajdi Zaghouani
Venue:
WANLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
192–198
Language:
URL:
https://aclanthology.org/W19-4621
DOI:
10.18653/v1/W19-4621
Bibkey:
Cite (ACL):
Ibrahim Abu Farha and Walid Magdy. 2019. Mazajak: An Online Arabic Sentiment Analyser. In Proceedings of the Fourth Arabic Natural Language Processing Workshop, pages 192–198, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Mazajak: An Online Arabic Sentiment Analyser (Abu Farha & Magdy, WANLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4621.pdf
Data
ASTD