SU-NLP at SemEval-2020 Task 12: Offensive Language Identification in Turkish Tweets

13Citations
Citations of this article
64Readers
Mendeley users who have this article in their library.

Abstract

This paper summarizes our group's efforts in the offensive language identification shared task, which is organized as part of the International Workshop on Semantic Evaluation (Sem-Eval2020). Our final submission system is an ensemble of three different models, (1) CNN-LSTM, (2) BiLSTM-Attention and (3) BERT. Word embeddings, which were pre-trained on tweets, are used while training the first two models. BERTurk, which is the first BERT model for Turkish, is also explored. Our final submitted approach ranked as the second best model in the Turkish sub-task.

Cite

CITATION STYLE

APA

Özdemir, A., & Yeniterzi, R. (2020). SU-NLP at SemEval-2020 Task 12: Offensive Language Identification in Turkish Tweets. In 14th International Workshops on Semantic Evaluation, SemEval 2020 - co-located 28th International Conference on Computational Linguistics, COLING 2020, Proceedings (pp. 2171–2176). International Committee for Computational Linguistics. https://doi.org/10.18653/v1/2020.semeval-1.288

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free