@inproceedings{zirikly-etal-2019-clpsych,
    title = "{CLP}sych 2019 Shared Task: Predicting the Degree of Suicide Risk in {R}eddit Posts",
    author = {Zirikly, Ayah  and
      Resnik, Philip  and
      Uzuner, {\"O}zlem  and
      Hollingshead, Kristy},
    editor = "Niederhoffer, Kate  and
      Hollingshead, Kristy  and
      Resnik, Philip  and
      Resnik, Rebecca  and
      Loveys, Kate",
    booktitle = "Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest_wac_2008/W19-3003/",
    doi = "10.18653/v1/W19-3003",
    pages = "24--33",
    abstract = "The shared task for the 2019 Workshop on Computational Linguistics and Clinical Psychology (CLPsych`19) introduced an assessment of suicide risk based on social media postings, using data from Reddit to identify users at no, low, moderate, or severe risk. Two variations of the task focused on users whose posts to the r/SuicideWatch subreddit indicated they might be at risk; a third task looked at screening users based only on their more everyday (non-SuicideWatch) posts. We received submissions from 15 different teams, and the results provide progress and insight into the value of language signal in helping to predict risk level."
}