@inproceedings{karan-snajder-2019-preemptive,
    title = "Preemptive Toxic Language Detection in {W}ikipedia Comments Using Thread-Level Context",
    author = "Karan, Vanja Mladen  and
      {\v{S}}najder, Jan",
    editor = "Roberts, Sarah T.  and
      Tetreault, Joel  and
      Prabhakaran, Vinodkumar  and
      Waseem, Zeerak",
    booktitle = "Proceedings of the Third Workshop on Abusive Language Online",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W19-3514/",
    doi = "10.18653/v1/W19-3514",
    pages = "129--134",
    abstract = "We address the task of automatically detecting toxic content in user generated texts. We fo cus on exploring the potential for preemptive moderation, i.e., predicting whether a particular conversation thread will, in the future, incite a toxic comment. Moreover, we perform preliminary investigation of whether a model that jointly considers all comments in a conversation thread outperforms a model that considers only individual comments. Using an existing dataset of conversations among Wikipedia contributors as a starting point, we compile a new large-scale dataset for this task consisting of labeled comments and comments from their conversation threads."
}