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

• URL: http://arxiv.org/abs/2008.01354v1
• Date: Tue, 4 Aug 2020 06:20:50 GMT
• Title: NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual Transfer
• Authors: Hwijeen Ahn and Jimin Sun and Chan Young Park and Jungyun Seo
• Abstract summary: 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. Our multilingual systems achieved competitive results in Greek, Danish, and Turkish at OffensEval 2020.
• Score: 10.007363787391952
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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