macech at SemEval-2021 Task 5: Toxic Spans Detection

Maggie Cech


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.
Anthology ID:
2021.semeval-1.137
Volume:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP | SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1003–1008
Language:
URL:
https://aclanthology.org/2021.semeval-1.137
DOI:
10.18653/v1/2021.semeval-1.137
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.137.pdf