Improving Moderation of Online Discussions via Interpretable Neural Models

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Abstract

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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APA

Švec, A., Pikuliak, M., Šimko, M., & Bieliková, M. (2018). Improving Moderation of Online Discussions via Interpretable Neural Models. In 2nd Workshop on Abusive Language Online - Proceedings of the Workshop, co-located with EMNLP 2018 (pp. 60–65). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w18-5108

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