@inproceedings{mut-altin-etal-2019-lastus,
    title = "{L}a{STUS}/{TALN} at {S}em{E}val-2019 Task 6: Identification and Categorization of Offensive Language in Social Media with Attention-based {B}i-{LSTM} model",
    author = "Mut Altin, Lutfiye Seda  and
      Bravo Serrano, {\`A}lex  and
      Saggion, Horacio",
    editor = "May, Jonathan  and
      Shutova, Ekaterina  and
      Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.",
    booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/S19-2120/",
    doi = "10.18653/v1/S19-2120",
    pages = "672--677",
    abstract = "We present a bidirectional Long-Short Term Memory network for identifying offensive language in Twitter. Our system has been developed in the context of the SemEval 2019 Task 6 which comprises three different sub-tasks, namely A: Offensive Language Detection, B: Categorization of Offensive Language, C: Offensive Language Target Identification. We used a pre-trained Word Embeddings in tweet data, including information about emojis and hashtags. Our approach achieves good performance in the three sub-tasks."
}