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
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W19-4621.pdf
- Data
- ASTD