@inproceedings{cech-2021-macech,
title = "macech at {S}em{E}val-2021 Task 5: Toxic Spans Detection",
author = "Cech, Maggie",
editor = "Palmer, Alexis and
Schneider, Nathan and
Schluter, Natalie and
Emerson, Guy and
Herbelot, Aurelie and
Zhu, Xiaodan",
booktitle = "Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.semeval-1.137",
doi = "10.18653/v1/2021.semeval-1.137",
pages = "1003--1008",
abstract = "Toxic language is often present in online forums, especially when politics and other polarizing topics arise, and can lead to people becoming discouraged from joining or continuing conversations. In this paper, we use data consisting of comments with the indices of toxic text labelled to train an RNN to deter-mine which parts of the comments make them toxic, which could aid online moderators. We compare results using both the original dataset and an augmented set, as well as GRU versus LSTM RNN models.",
}
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%0 Conference Proceedings
%T macech at SemEval-2021 Task 5: Toxic Spans Detection
%A Cech, Maggie
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Schluter, Natalie
%Y Emerson, Guy
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%S Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F cech-2021-macech
%X Toxic language is often present in online forums, especially when politics and other polarizing topics arise, and can lead to people becoming discouraged from joining or continuing conversations. In this paper, we use data consisting of comments with the indices of toxic text labelled to train an RNN to deter-mine which parts of the comments make them toxic, which could aid online moderators. We compare results using both the original dataset and an augmented set, as well as GRU versus LSTM RNN models.
%R 10.18653/v1/2021.semeval-1.137
%U https://aclanthology.org/2021.semeval-1.137
%U https://doi.org/10.18653/v1/2021.semeval-1.137
%P 1003-1008
Markdown (Informal)
[macech at SemEval-2021 Task 5: Toxic Spans Detection](https://aclanthology.org/2021.semeval-1.137) (Cech, SemEval 2021)
ACL