@inproceedings{abu-farha-magdy-2019-mazajak,
title = "{M}azajak: An Online {A}rabic Sentiment Analyser",
author = "Abu Farha, Ibrahim and
Magdy, Walid",
editor = "El-Hajj, Wassim and
Belguith, Lamia Hadrich and
Bougares, Fethi and
Magdy, Walid and
Zitouni, Imed and
Tomeh, Nadi and
El-Haj, Mahmoud and
Zaghouani, Wajdi",
booktitle = "Proceedings of the Fourth Arabic Natural Language Processing Workshop",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-4621",
doi = "10.18653/v1/W19-4621",
pages = "192--198",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Mazajak: An Online Arabic Sentiment Analyser
%A Abu Farha, Ibrahim
%A Magdy, Walid
%Y El-Hajj, Wassim
%Y Belguith, Lamia Hadrich
%Y Bougares, Fethi
%Y Magdy, Walid
%Y Zitouni, Imed
%Y Tomeh, Nadi
%Y El-Haj, Mahmoud
%Y Zaghouani, Wajdi
%S Proceedings of the Fourth Arabic Natural Language Processing Workshop
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F abu-farha-magdy-2019-mazajak
%X 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.
%R 10.18653/v1/W19-4621
%U https://aclanthology.org/W19-4621
%U https://doi.org/10.18653/v1/W19-4621
%P 192-198
Markdown (Informal)
[Mazajak: An Online Arabic Sentiment Analyser](https://aclanthology.org/W19-4621) (Abu Farha & Magdy, WANLP 2019)
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.