@inproceedings{rajendran-etal-2019-ubc,
    title = "{UBC}-{NLP} at {S}em{E}val-2019 Task 6: Ensemble Learning of Offensive Content With Enhanced Training Data",
    author = "Rajendran, Arun  and
      Zhang, Chiyu  and
      Abdul-Mageed, Muhammad",
    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/jlcl-multiple-ingestion/S19-2136/",
    doi = "10.18653/v1/S19-2136",
    pages = "775--781",
    abstract = "We examine learning offensive content on Twitter with limited, imbalanced data. For the purpose, we investigate the utility of using various data enhancement methods with a host of classical ensemble classifiers. Among the 75 participating teams in SemEval-2019 sub-task B, our system ranks 6th (with 0.706 macro F1-score). For sub-task C, among the 65 participating teams, our system ranks 9th (with 0.587 macro F1-score)."
}