NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual Transfer

Hwijeen Ahn, Jimin Sun, Chan Young Park, Jungyun Seo


Abstract
This paper describes our approach to the task of identifying offensive languages in a multilingual setting. We investigate two data augmentation strategies: using additional semi-supervised labels with different thresholds and cross-lingual transfer with data selection. Leveraging the semi-supervised dataset resulted in performance improvements compared to the baseline trained solely with the manually-annotated dataset. We propose a new metric, Translation Embedding Distance, to measure the transferability of instances for cross-lingual data selection. We also introduce various preprocessing steps tailored for social media text along with methods to fine-tune the pre-trained multilingual BERT (mBERT) for offensive language identification. Our multilingual systems achieved competitive results in Greek, Danish, and Turkish at OffensEval 2020.
Anthology ID:
2020.semeval-1.206
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Venues:
COLING | SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
1576–1586
Language:
URL:
https://aclanthology.org/2020.semeval-1.206
DOI:
10.18653/v1/2020.semeval-1.206
Bibkey:
Cite (ACL):
Hwijeen Ahn, Jimin Sun, Chan Young Park, and Jungyun Seo. 2020. NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual Transfer. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1576–1586, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual Transfer (Ahn et al., SemEval 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.semeval-1.206.pdf
Code
 hwijeen/OffensEval2020
Data
OLID