@inproceedings{park-fung-2017-one,
    title = "One-step and Two-step Classification for Abusive Language Detection on {T}witter",
    author = "Park, Ji Ho  and
      Fung, Pascale",
    editor = "Waseem, Zeerak  and
      Chung, Wendy Hui Kyong  and
      Hovy, Dirk  and
      Tetreault, Joel",
    booktitle = "Proceedings of the First Workshop on Abusive Language Online",
    month = aug,
    year = "2017",
    address = "Vancouver, BC, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W17-3006/",
    doi = "10.18653/v1/W17-3006",
    pages = "41--45",
    abstract = "Automatic abusive language detection is a difficult but important task for online social media. Our research explores a two-step approach of performing classification on abusive language and then classifying into specific types and compares it with one-step approach of doing one multi-class classification for detecting sexist and racist languages. With a public English Twitter corpus of 20 thousand tweets in the type of sexism and racism, our approach shows a promising performance of 0.827 F-measure by using HybridCNN in one-step and 0.824 F-measure by using logistic regression in two-steps."
}