Mazajak: An Online Arabic Sentiment Analyser

Ibrahim Abu Farha; Walid Magdy

doi:10.18653/v1/W19-4621

Mazajak: An Online Arabic Sentiment Analyser

Ibrahim Abu Farha, Walid Magdy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

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-theart 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.

Original language	English
Title of host publication	Proceedings of the Fourth Arabic Natural Language Processing Workshop
Publisher	Association for Computational Linguistics (ACL)
Pages	192-198
Number of pages	7
ISBN (Electronic)	978-1-950737-32-1
DOIs	https://doi.org/10.18653/v1/W19-4621
Publication status	Accepted/In press - 24 May 2019
Event	The Fourth Arabic Natural Language Processing Workshop - Florence, Italy Duration: 1 Aug 2019 → 2 Aug 2019 Conference number: 4 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=83625&copyownerid=320

Workshop

Workshop	The Fourth Arabic Natural Language Processing Workshop
Abbreviated title	WANLP 2019
Country/Territory	Italy
City	Florence
Period	1/08/19 → 2/08/19
Internet address	http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=83625&copyownerid=320

Access to Document

10.18653/v1/W19-4621Licence: Creative Commons: Attribution (CC-BY)

Mazajak An Online Arabic_MAGDY_DoA240519_AFVAccepted author manuscript, 368 KB
Mazajak An Online _ABU FARHA_DOA25102019_VOR_CC-BYFinal published version, 439 KBLicence: Creative Commons: Attribution (CC-BY)

https://www.aclweb.org/anthology/W19-4621/Licence: Creative Commons: Attribution (CC-BY)

Cite this

@inproceedings{bc32529dad9f4d189b8939f68760e02d,

title = "Mazajak: An Online Arabic Sentiment Analyser",

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-theart 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.",

author = "{Abu Farha}, Ibrahim and Walid Magdy",

year = "2019",

month = may,

day = "24",

doi = "10.18653/v1/W19-4621",

language = "English",

pages = "192--198",

booktitle = "Proceedings of the Fourth Arabic Natural Language Processing Workshop",

publisher = "Association for Computational Linguistics (ACL)",

note = "The Fourth Arabic Natural Language Processing Workshop, WANLP 2019 ; Conference date: 01-08-2019 Through 02-08-2019",

url = "http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=83625&copyownerid=320",

}

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T1 - Mazajak: An Online Arabic Sentiment Analyser

AU - Abu Farha, Ibrahim

AU - Magdy, Walid

N1 - Conference code: 4

PY - 2019/5/24

Y1 - 2019/5/24

N2 - 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-theart 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.

AB - 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-theart 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.

U2 - 10.18653/v1/W19-4621

DO - 10.18653/v1/W19-4621

M3 - Conference contribution

SP - 192

EP - 198

BT - Proceedings of the Fourth Arabic Natural Language Processing Workshop

PB - Association for Computational Linguistics (ACL)

T2 - The Fourth Arabic Natural Language Processing Workshop

Y2 - 1 August 2019 through 2 August 2019

ER -

Mazajak: An Online Arabic Sentiment Analyser

Abstract / Description of output

Workshop

Access to Document

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Cite this