Improving Moderation of Online Discussions via Interpretable Neural Models

Andrej \v{S}vec; Bratislava; M\'aria Bielikov\'a (Slovak University of Technology in Bratislava; Mari\'an \v{S}imko; Mat\'u\v{s} Pikuliak; Slovakia)

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Improving Moderation of Online Discussions via Interpretable Neural Models

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arxiv 1809.06906 v1 pith:OJLTB7VE submitted 2018-09-18 cs.CL

Andrej Švec , Matúš Pikuliak , Marián Šimko , Mária Bieliková (Slovak University of Technology in Bratislava , Bratislava , Slovakia) This is my paper

classification cs.CL

keywords commentsmoderationdiscussiondiscussionsinappropriatemakemethodmoderators

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Growing amount of comments make online discussions difficult to moderate by human moderators only. Antisocial behavior is a common occurrence that often discourages other users from participating in discussion. We propose a neural network based method that partially automates the moderation process. It consists of two steps. First, we detect inappropriate comments for moderators to see. Second, we highlight inappropriate parts within these comments to make the moderation faster. We evaluated our method on data from a major Slovak news discussion platform.

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