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    <abstract>Content moderators play a key role in keeping the conversation on social media healthy. While the high volume of content they need to judge represents a bottleneck to the moderation pipeline, no studies have explored how models could support them to make faster decisions. There is, by now, a vast body of research into detecting hate speech, sometimes explicitly motivated by a desire to help improve content moderation, but published research using real content moderators is scarce. In this work we investigate the effect of explanations on the speed of real-world moderators. Our experiments show that while generic explanations do not affect their speed and are often ignored, structured explanations lower moderators’ decision making time by 7.4%.</abstract>
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%0 Conference Proceedings
%T Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster
%A Calabrese, Agostina
%A Neves, Leonardo
%A Shah, Neil
%A Bos, Maarten
%A Ross, Björn
%A Lapata, Mirella
%A Barbieri, Francesco
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F calabrese-etal-2024-explainability
%X Content moderators play a key role in keeping the conversation on social media healthy. While the high volume of content they need to judge represents a bottleneck to the moderation pipeline, no studies have explored how models could support them to make faster decisions. There is, by now, a vast body of research into detecting hate speech, sometimes explicitly motivated by a desire to help improve content moderation, but published research using real content moderators is scarce. In this work we investigate the effect of explanations on the speed of real-world moderators. Our experiments show that while generic explanations do not affect their speed and are often ignored, structured explanations lower moderators’ decision making time by 7.4%.
%U https://aclanthology.org/2024.acl-short.38
%P 398-408

Markdown (Informal)

[Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster](https://aclanthology.org/2024.acl-short.38) (Calabrese et al., ACL 2024)

• Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster (Calabrese et al., ACL 2024)

ACL

• Agostina Calabrese, Leonardo Neves, Neil Shah, Maarten Bos, Björn Ross, Mirella Lapata, and Francesco Barbieri. 2024. Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 398–408, Bangkok, Thailand. Association for Computational Linguistics.