Community-level Research on Suicidality Prediction in a Secure Environment: Overview of the CLPsych 2021 Shared Task
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Philip Resnik | Glen Coppersmith | Sean MacAvaney | Anjali Mittu | Jeff Leintz | P. Resnik | Glen A. Coppersmith | Sean MacAvaney | Jeff Leintz | Anjali Mittu
[1] Lawrence R. Rabiner,et al. Automatic Speech Recognition - A Brief History of the Technology Development , 2004 .
[2] Alex B. Fine,et al. Natural Language Processing of Social Media as Screening for Suicide Risk , 2018, Biomedical informatics insights.
[3] P. Resnik,et al. CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts , 2019, Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology.
[4] P. Resnik,et al. A direct comparison of theory-driven and machine learning prediction of suicide: A meta-analysis , 2021, PloS one.
[5] Timothy Baldwin,et al. An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation , 2016, Rep4NLP@ACL.
[6] F. Ritchie. The ‘Five Safes’: A framework for planning, designing and evaluating data access solutions , 2017 .
[7] Mark Dredze,et al. Quantifying Mental Health Signals in Twitter , 2014, CLPsych@ACL.
[8] T. Yarkoni,et al. Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning , 2017, Perspectives on psychological science : a journal of the Association for Psychological Science.
[9] Nazli Goharian,et al. Depression and Self-Harm Risk Assessment in Online Forums , 2017, EMNLP.
[10] Evan M. Kleiman,et al. Risk Factors for Suicidal Thoughts and Behaviors: A Meta-Analysis of 50 Years of Research , 2017, Psychological bulletin.
[11] Peter Szolovits,et al. MIMIC-III, a freely accessible critical care database , 2016, Scientific Data.
[12] P. Resnik,et al. Naturally occurring language as a source of evidence in suicide prevention. , 2020, Suicide & life-threatening behavior.
[13] Julia Lane,et al. Balancing access to health data and privacy: a review of the issues and approaches for the future. , 2010, Health services research.
[14] Ryan L. Boyd,et al. The Development and Psychometric Properties of LIWC2015 , 2015 .
[15] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[16] Glen Coppersmith,et al. Exploratory Analysis of Social Media Prior to a Suicide Attempt , 2016, CLPsych@HLT-NAACL.
[17] Munmun De Choudhury,et al. A Taxonomy of Ethical Tensions in Inferring Mental Health States from Social Media , 2019, FAT.
[18] Mark Dredze,et al. Shared Task : Depression and PTSD on Twitter , 2015 .
[19] Philip Resnik,et al. Expert, Crowdsourced, and Machine Assessment of Suicide Risk via Online Postings , 2018, CLPsych@NAACL-HTL.
[20] See-Kiong Ng,et al. Suicide Risk Prediction by Tracking Self-Harm Aspects in Tweets: NUS-IDS at the CLPsych 2021 Shared Task , 2021, CLPSYCH.
[21] J. Naslund,et al. Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice , 2020, Journal of Technology in Behavioral Science.
[22] Almog Simchon,et al. Using Psychologically-Informed Priors for Suicide Prediction in the CLPsych 2021 Shared Task , 2021, CLPSYCH.
[23] Barbara J. Grosz,et al. Natural-Language Processing , 1982, Artificial Intelligence.
[24] Iz Beltagy,et al. SciBERT: A Pretrained Language Model for Scientific Text , 2019, EMNLP.
[25] E. Horvitz,et al. Data, privacy, and the greater good , 2015, Science.
[26] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[27] Kriti Kohli,et al. Team 9: A Comparison of Simple vs. Complex Models for Suicide Risk Assessment , 2021, CLPSYCH.
[28] Determining a Person’s Suicide Risk by Voting on the Short-Term History of Tweets for the CLPsych 2021 Shared Task , 2021, CLPSYCH.
[29] Wei-Hung Weng,et al. Publicly Available Clinical BERT Embeddings , 2019, Proceedings of the 2nd Clinical Natural Language Processing Workshop.
[30] D. Asch,et al. Facebook language predicts depression in medical records , 2018, Proceedings of the National Academy of Sciences.
[31] K. P. Subbalakshmi,et al. Learning Models for Suicide Prediction from Social Media Posts , 2021, CLPSYCH.
[32] Lucila Ohno-Machado,et al. Natural language processing: an introduction , 2011, J. Am. Medical Informatics Assoc..
[33] C. Depp,et al. Artificial Intelligence for Mental Healthcare: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom. , 2021, Biological psychiatry. Cognitive neuroscience and neuroimaging.
[34] Munmun De Choudhury,et al. Methodological Gaps in Predicting Mental Health States from Social Media: Triangulating Diagnostic Signals , 2019, CHI.
[35] Munmun De Choudhury,et al. Mental Health Discourse on reddit: Self-Disclosure, Social Support, and Anonymity , 2014, ICWSM.
[36] Bart Desmet,et al. SMHD: a Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions , 2018, COLING.
[37] Phillip Wolff,et al. Predicting future mental illness from social media: A big-data approach , 2019, Behavior research methods.
[38] Mark Dredze,et al. Ethical Research Protocols for Social Media Health Research , 2017, EthNLP@EACL.
[39] Mark Dredze,et al. Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media , 2016, CHI.