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        <title>ASAD: Arabic Social media Analytics and unDerstanding</title>
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        <namePart type="given">Hamdy</namePart>
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    <name type="personal">
        <namePart type="given">Kareem</namePart>
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            <title>Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations</title>
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            <namePart type="given">Dimitra</namePart>
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    <abstract>This system demonstration paper describes ASAD: Arabic Social media Analysis and unDerstanding, a suite of seven individual modules that allows users to determine dialects, sentiment, news category, offensiveness, hate speech, adult content, and spam in Arabic tweets. The suite is made available through a web API and a web interface where users can enter text or upload files.</abstract>
    <identifier type="citekey">hassan-etal-2021-asad</identifier>
    <identifier type="doi">10.18653/v1/2021.eacl-demos.14</identifier>
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        <date>2021-04</date>
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%0 Conference Proceedings
%T ASAD: Arabic Social media Analytics and unDerstanding
%A Hassan, Sabit
%A Mubarak, Hamdy
%A Abdelali, Ahmed
%A Darwish, Kareem
%Y Gkatzia, Dimitra
%Y Seddah, Djamé
%S Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F hassan-etal-2021-asad
%X This system demonstration paper describes ASAD: Arabic Social media Analysis and unDerstanding, a suite of seven individual modules that allows users to determine dialects, sentiment, news category, offensiveness, hate speech, adult content, and spam in Arabic tweets. The suite is made available through a web API and a web interface where users can enter text or upload files.
%R 10.18653/v1/2021.eacl-demos.14
%U https://aclanthology.org/2021.eacl-demos.14
%U https://doi.org/10.18653/v1/2021.eacl-demos.14
%P 113-118

Markdown (Informal)

[ASAD: Arabic Social media Analytics and unDerstanding](https://aclanthology.org/2021.eacl-demos.14) (Hassan et al., EACL 2021)

• ASAD: Arabic Social media Analytics and unDerstanding (Hassan et al., EACL 2021)

ACL

• Sabit Hassan, Hamdy Mubarak, Ahmed Abdelali, and Kareem Darwish. 2021. ASAD: Arabic Social media Analytics and unDerstanding. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 113–118, Online. Association for Computational Linguistics.