@inproceedings{ozdemir-yeniterzi-2020-su,
    title = "{SU}-{NLP} at {S}em{E}val-2020 Task 12: Offensive Language {I}dentifi{C}ation in {T}urkish Tweets",
    author = "Ozdemir, Anil  and
      Yeniterzi, Reyyan",
    editor = "Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Palmer, Alexis  and
      Schneider, Nathan  and
      May, Jonathan  and
      Shutova, Ekaterina",
    booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
    month = dec,
    year = "2020",
    address = "Barcelona (online)",
    publisher = "International Committee for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.semeval-1.288/",
    doi = "10.18653/v1/2020.semeval-1.288",
    pages = "2171--2176",
    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."
}