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        <title>Delete or not Delete? Semi-Automatic Comment Moderation for the Newsroom</title>
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            <namePart type="given">Ritesh</namePart>
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    <abstract>Comment sections of online news providers have enabled millions to share and discuss their opinions on news topics. Today, moderators ensure respectful and informative discussions by deleting not only insults, defamation, and hate speech, but also unverifiable facts. This process has to be transparent and comprehensive in order to keep the community engaged. Further, news providers have to make sure to not give the impression of censorship or dissemination of fake news. Yet manual moderation is very expensive and becomes more and more unfeasible with the increasing amount of comments. Hence, we propose a semi-automatic, holistic approach, which includes comment features but also their context, such as information about users and articles. For evaluation, we present experiments on a novel corpus of 3 million news comments annotated by a team of professional moderators.</abstract>
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%0 Conference Proceedings
%T Delete or not Delete? Semi-Automatic Comment Moderation for the Newsroom
%A Risch, Julian
%A Krestel, Ralf
%Y Kumar, Ritesh
%Y Ojha, Atul Kr.
%Y Zampieri, Marcos
%Y Malmasi, Shervin
%S Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018)
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F risch-krestel-2018-delete
%X Comment sections of online news providers have enabled millions to share and discuss their opinions on news topics. Today, moderators ensure respectful and informative discussions by deleting not only insults, defamation, and hate speech, but also unverifiable facts. This process has to be transparent and comprehensive in order to keep the community engaged. Further, news providers have to make sure to not give the impression of censorship or dissemination of fake news. Yet manual moderation is very expensive and becomes more and more unfeasible with the increasing amount of comments. Hence, we propose a semi-automatic, holistic approach, which includes comment features but also their context, such as information about users and articles. For evaluation, we present experiments on a novel corpus of 3 million news comments annotated by a team of professional moderators.
%U https://aclanthology.org/W18-4420
%P 166-176

Markdown (Informal)

[Delete or not Delete? Semi-Automatic Comment Moderation for the Newsroom](https://aclanthology.org/W18-4420) (Risch & Krestel, TRAC 2018)

• Delete or not Delete? Semi-Automatic Comment Moderation for the Newsroom (Risch & Krestel, TRAC 2018)

ACL

• Julian Risch and Ralf Krestel. 2018. Delete or not Delete? Semi-Automatic Comment Moderation for the Newsroom. In Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pages 166–176, Santa Fe, New Mexico, USA. Association for Computational Linguistics.