CSECU-DSG at SemEval-2021 Task 5: Leveraging Ensemble of Sequence Tagging Models for Toxic Spans Detection

Tashin Hossain, Jannatun Naim, Fareen Tasneem, Radiathun Tasnia, Abu Nowshed Chy


Abstract
The upsurge of prolific blogging and microblogging platforms enabled the abusers to spread negativity and threats greater than ever. Detecting the toxic portions substantially aids to moderate or exclude the abusive parts for maintaining sound online platforms. This paper describes our participation in the SemEval 2021 toxic span detection task. The task requires detecting spans that convey toxic remarks from the given text. We explore an ensemble of sequence labeling models including the BiLSTM-CRF, spaCy NER model with custom toxic tags, and fine-tuned BERT model to identify the toxic spans. Finally, a majority voting ensemble method is used to determine the unified toxic spans. Experimental results depict the competitive performance of our model among the participants.
Anthology ID:
2021.semeval-1.135
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:
990–994
Language:
URL:
https://aclanthology.org/2021.semeval-1.135
DOI:
10.18653/v1/2021.semeval-1.135
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.135.pdf