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        <title>Adult Content Detection on Arabic Twitter: Analysis and Experiments</title>
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        <namePart type="given">Hamdy</namePart>
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    <abstract>With Twitter being one of the most popular social media platforms in the Arab region, it is not surprising to find accounts that post adult content in Arabic tweets; despite the fact that these platforms dissuade users from such content. In this paper, we present a dataset of Twitter accounts that post adult content. We perform an in-depth analysis of the nature of this data and contrast it with normal tweet content. Additionally, we present extensive experiments with traditional machine learning models, deep neural networks and contextual embeddings to identify such accounts. We show that from user information alone, we can identify such accounts with F1 score of 94.7% (macro average). With the addition of only one tweet as input, the F1 score rises to 96.8%.</abstract>
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        <date>2021-04</date>
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%0 Conference Proceedings
%T Adult Content Detection on Arabic Twitter: Analysis and Experiments
%A Mubarak, Hamdy
%A Hassan, Sabit
%A Abdelali, Ahmed
%S Proceedings of the Sixth Arabic Natural Language Processing Workshop
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kyiv, Ukraine (Virtual)
%F mubarak-etal-2021-adult
%X With Twitter being one of the most popular social media platforms in the Arab region, it is not surprising to find accounts that post adult content in Arabic tweets; despite the fact that these platforms dissuade users from such content. In this paper, we present a dataset of Twitter accounts that post adult content. We perform an in-depth analysis of the nature of this data and contrast it with normal tweet content. Additionally, we present extensive experiments with traditional machine learning models, deep neural networks and contextual embeddings to identify such accounts. We show that from user information alone, we can identify such accounts with F1 score of 94.7% (macro average). With the addition of only one tweet as input, the F1 score rises to 96.8%.
%U https://aclanthology.org/2021.wanlp-1.14
%P 136-144

Markdown (Informal)

[Adult Content Detection on Arabic Twitter: Analysis and Experiments](https://aclanthology.org/2021.wanlp-1.14) (Mubarak et al., WANLP 2021)

• Adult Content Detection on Arabic Twitter: Analysis and Experiments (Mubarak et al., WANLP 2021)

ACL

• Hamdy Mubarak, Sabit Hassan, and Ahmed Abdelali. 2021. Adult Content Detection on Arabic Twitter: Analysis and Experiments. In Proceedings of the Sixth Arabic Natural Language Processing Workshop, pages 136–144, Kyiv, Ukraine (Virtual). Association for Computational Linguistics.