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Naturally occurring language as a source of evidence in suicide prevention
Author(s) -
Resnik Philip,
Foreman April,
Kuchuk Michelle,
Musacchio Schafer Katherine,
Pinkham Beau
Publication year - 2021
Publication title -
suicide and life‐threatening behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.544
H-Index - 90
eISSN - 1943-278X
pISSN - 0363-0234
DOI - 10.1111/sltb.12674
Subject(s) - suicide prevention , poison control , human factors and ergonomics , injury prevention , occupational safety and health , psychology , value (mathematics) , relation (database) , computer security , medicine , computer science , medical emergency , data mining , pathology , machine learning
We discuss computational language analysis as it pertains to suicide prevention research, with an emphasis on providing non‐technologists with an understanding of key issues and, equally important, considering its relation to the broader enterprise of suicide prevention. Our emphasis here is on naturally occurring language in social media, motivated by its non‐intrusive ability to yield high‐value information that in the past has been largely unavailable to clinicians.