Delete or not Delete? Semi-Automatic Comment Moderation for the Newsroom

Julian Risch, Ralf Krestel


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.
Anthology ID:
W18-4420
Volume:
Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018)
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Venues:
COLING | TRAC | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
166–176
Language:
URL:
https://aclanthology.org/W18-4420
DOI:
Bibkey:
Cite (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.
Cite (Informal):
Delete or not Delete? Semi-Automatic Comment Moderation for the Newsroom (Risch & Krestel, 2018)
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PDF:
https://aclanthology.org/W18-4420.pdf