Question Answering for Suicide Risk Assessment using Reddit

TitleQuestion Answering for Suicide Risk Assessment using Reddit
Publication TypeConference Paper
Year of Publication2019
AuthorsAmanuel Alambo, Manas Gaur, Usha Lokala, Ugur Kursuncu, Thirunarayam, K, Amelie Gyrard, Randall Hand, Jyotishman Pathak, Amit Sheth
Conference Name13th IEEE International Conference on Semantic Computing
Date Published02/02/2019
PublisherIEEE
Conference LocationNewport Beach, California
KeywordsC-SSRS, Reddit, Semantic Machine Learning, Semantic Social Computing, Suicide Risk Assessment, The Diagnostic and Statistical Manual of Mental Disorders – Fifth Edition (DSM-5), Web-based Intervention
Abstract

Mental Health America designed ten questionnaires that are used to determine the risk of mental disorders. They are also commonly used by Mental Health Professionals (MHPs) to assess suicidality. Specifically, the Columbia Suicide Severity Rating Scale (C-SSRS), a widely used suicide assessment questionnaire, helps MHPs determine the severity of suicide risk and offer an appropriate treatment. A major challenge in suicide treatment is the social stigma wherein the patient feels reluctance in discussing his/her conditions with an MHP, which leads to inaccurate assessment and treatment of patients. On the other hand, the same patient is comfortable freely discussing his/her mental health condition on social media due to the anonymity of platforms such as Reddit, and the ability to control what, when and how to share.
The popular “SuicideWatch” subreddit has been widely used among individuals who experience suicidal thoughts, and provides significant cues for suicidality. The timeliness in sharing thoughts, the flexibility in describing feelings, and the interoperability in using medical terminologies make Reddit an important platform to be utilized as a complementary tool to the conventional healthcare system. As MHPs develop an implicit weighting scheme over the questionnaire (i.e., C-SSRS) to assess suicide risk severity, creating a relative weighting scheme for answers to be automatically generated to the questions in the questionnaire poses as a key challenge. In this interdisciplinary study, we position our approach towards a solution for an automated suicide risk elicitation framework through a novel question answering mechanism. Our two-fold approach benefits from using: 1) semantic clustering, and 2) sequence-to-sequence (Seq2Seq) models. We also generate a gold standard dataset of suicide posts with their risk levels. This work forms a basis for the next step of building conversational agents that elicit suicide-related natural conversation based on questions.

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Citation:
Amanuel Alambo, Manas Gaur, Usha Lokala, Ugur Kursuncu, Krishnaprasad Thirunarayan, Amelie Gyrard, Randon S. Welton, Jyotishman Pathak, Amit Sheth."Question Answering for Suicide Risk Assessment using Reddit".13th IEEE International Conference on Semantic Computing (2019). Newport Beach, California.

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