Abusive Language Detection on Arabic Social Media

Hamdy Mubarak, Kareem Darwish, Walid Magdy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present our work on detecting abusive language on Arabic social media. We extract a list of obscene words and hashtags using common patterns used in offensive and rude communications. We also classify Twitter users according to whether they use any of these words or not in their tweets. We expand the list of obscene words using this classification, and we report results on a newly created dataset of classified Arabic tweets (obscene, offensive, and clean). We make this dataset freely available for research, in addition to the list of obscene words and hashtags. We are also publicly releasing a large corpus of classified user comments that were deleted from a popular Arabic news site due to violations the site’s rules and guidelines.
Original languageEnglish
Title of host publicationProceedings of the First Workshop on Abusive Language Online
PublisherAssociation for Computational Linguistics (ACL)
Pages52–56
Number of pages5
ISBN (Print)978-1-945626-66-1
DOIs
Publication statusPublished - 4 Aug 2017
EventFirst Workshop on Abusive Language Online 2017 - Vancouver, Canada
Duration: 4 Aug 20174 Aug 2017
https://sites.google.com/site/abusivelanguageworkshop2017/

Conference

ConferenceFirst Workshop on Abusive Language Online 2017
Abbreviated titleALW1 2017
Country/TerritoryCanada
CityVancouver
Period4/08/174/08/17
Internet address

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