Ayah Zirikly, P. Resnik, Özlem Uzuner, Kristy Hollingshead
{"title":"CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts","authors":"Ayah Zirikly, P. Resnik, Özlem Uzuner, Kristy Hollingshead","doi":"10.18653/v1/W19-3003","DOIUrl":null,"url":null,"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.","PeriodicalId":201097,"journal":{"name":"Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"156","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/W19-3003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 156
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.