@inproceedings{andersen-etal-2021-rem,
title = "{REM}: Efficient Semi-Automated Real-Time Moderation of Online Forums",
author = "Andersen, Jakob Smedegaard and
Zukunft, Olaf and
Maalej, Walid",
editor = "Ji, Heng and
Park, Jong C. and
Xia, Rui",
booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.acl-demo.17",
doi = "10.18653/v1/2021.acl-demo.17",
pages = "142--149",
abstract = "This paper presents REM, a novel tool for the semi-automated real-time moderation of large scale online forums. The growing demand for online participation and the increasing number of user comments raise challenges in filtering out harmful and undesirable content from public debates in online forums. Since a manual moderation does not scale well and pure automated approaches often lack the required level of accuracy, we suggest a semi-automated moderation approach. Our approach maximizes the efficiency of manual efforts by targeting only those comments for which human intervention is needed, e.g. due to high classification uncertainty. Our tool offers a rich visual interactive environment enabling the exploration of online debates. We conduct a preliminary evaluation experiment to demonstrate the suitability of our approach and publicly release the source code of REM.",
}
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<abstract>This paper presents REM, a novel tool for the semi-automated real-time moderation of large scale online forums. The growing demand for online participation and the increasing number of user comments raise challenges in filtering out harmful and undesirable content from public debates in online forums. Since a manual moderation does not scale well and pure automated approaches often lack the required level of accuracy, we suggest a semi-automated moderation approach. Our approach maximizes the efficiency of manual efforts by targeting only those comments for which human intervention is needed, e.g. due to high classification uncertainty. Our tool offers a rich visual interactive environment enabling the exploration of online debates. We conduct a preliminary evaluation experiment to demonstrate the suitability of our approach and publicly release the source code of REM.</abstract>
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%0 Conference Proceedings
%T REM: Efficient Semi-Automated Real-Time Moderation of Online Forums
%A Andersen, Jakob Smedegaard
%A Zukunft, Olaf
%A Maalej, Walid
%Y Ji, Heng
%Y Park, Jong C.
%Y Xia, Rui
%S Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F andersen-etal-2021-rem
%X This paper presents REM, a novel tool for the semi-automated real-time moderation of large scale online forums. The growing demand for online participation and the increasing number of user comments raise challenges in filtering out harmful and undesirable content from public debates in online forums. Since a manual moderation does not scale well and pure automated approaches often lack the required level of accuracy, we suggest a semi-automated moderation approach. Our approach maximizes the efficiency of manual efforts by targeting only those comments for which human intervention is needed, e.g. due to high classification uncertainty. Our tool offers a rich visual interactive environment enabling the exploration of online debates. We conduct a preliminary evaluation experiment to demonstrate the suitability of our approach and publicly release the source code of REM.
%R 10.18653/v1/2021.acl-demo.17
%U https://aclanthology.org/2021.acl-demo.17
%U https://doi.org/10.18653/v1/2021.acl-demo.17
%P 142-149
Markdown (Informal)
[REM: Efficient Semi-Automated Real-Time Moderation of Online Forums](https://aclanthology.org/2021.acl-demo.17) (Andersen et al., ACL-IJCNLP 2021)
ACL
- Jakob Smedegaard Andersen, Olaf Zukunft, and Walid Maalej. 2021. REM: Efficient Semi-Automated Real-Time Moderation of Online Forums. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations, pages 142–149, Online. Association for Computational Linguistics.