The Hitchhiker’s Guide to Computational Linguistics in Suicide Prevention
نویسندگان
چکیده
Suicide, a leading cause of death, is complex and hard-to-predict human tragedy. In this article, we introduce comprehensive outlook on the emerging movement to integrate computational linguistics (CL) in suicide prevention research practice. Focusing mainly state-of-the-art deep neural network models, “travel guide” describe, relatively plain language, how CL methodologies could facilitate early detection risk. Major potential contributions (e.g., word embeddings, interpretational frameworks) for deepening that theoretical understanding behaviors promoting personalized approach psychological assessment are presented as well. We also discuss principal ethical methodological obstacles prevention, such difficulty maintain people’s privacy/safety or interpret “black box” prediction algorithms. Ethical guidelines practical recommendations addressing these provided future researchers clinicians.
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ژورنال
عنوان ژورنال: Clinical psychological science
سال: 2021
ISSN: ['2167-7034', '2167-7026']
DOI: https://doi.org/10.1177/21677026211022013