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        <title>Deep Learning for User Comment Moderation</title>
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            <title>Proceedings of the First Workshop on Abusive Language Online</title>
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    <abstract>Experimenting with a new dataset of 1.6M user comments from a Greek news portal and existing datasets of EnglishWikipedia comments, we show that an RNN outperforms the previous state of the art in moderation. A deep, classification-specific attention mechanism improves further the overall performance of the RNN. We also compare against a CNN and a word-list baseline, considering both fully automatic and semi-automatic moderation.</abstract>
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%0 Conference Proceedings
%T Deep Learning for User Comment Moderation
%A Pavlopoulos, John
%A Malakasiotis, Prodromos
%A Androutsopoulos, Ion
%Y Waseem, Zeerak
%Y Chung, Wendy Hui Kyong
%Y Hovy, Dirk
%Y Tetreault, Joel
%S Proceedings of the First Workshop on Abusive Language Online
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, BC, Canada
%F pavlopoulos-etal-2017-deep
%X Experimenting with a new dataset of 1.6M user comments from a Greek news portal and existing datasets of EnglishWikipedia comments, we show that an RNN outperforms the previous state of the art in moderation. A deep, classification-specific attention mechanism improves further the overall performance of the RNN. We also compare against a CNN and a word-list baseline, considering both fully automatic and semi-automatic moderation.
%R 10.18653/v1/W17-3004
%U https://aclanthology.org/W17-3004
%U https://doi.org/10.18653/v1/W17-3004
%P 25-35

Markdown (Informal)

[Deep Learning for User Comment Moderation](https://aclanthology.org/W17-3004) (Pavlopoulos et al., ALW 2017)

• Deep Learning for User Comment Moderation (Pavlopoulos et al., ALW 2017)

ACL

• John Pavlopoulos, Prodromos Malakasiotis, and Ion Androutsopoulos. 2017. Deep Learning for User Comment Moderation. In Proceedings of the First Workshop on Abusive Language Online, pages 25–35, Vancouver, BC, Canada. Association for Computational Linguistics.