Methodology of Labeling According to 9 Criteria of DSM-5

Depression disorder is a disease that causes a deterioration of daily function and can induce thoughts of suicide. The Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5), which is the official reference of the American Psychiatry Association and is also used in Korea to iden...

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Bibliographic Details
Published inApplied sciences Vol. 13; no. 18; p. 10481
Main Authors Lee, Geonju, Park, Dabin, Oh, Hayoung
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2023
Subjects
Artificial intelligence
Computational linguistics
Datasets
Depression, Mental
Dictionaries
DSM-5
embedding
Emotions
Empathy
Evaluation
Health aspects
Language processing
Mental disorders
morphological analysis
multi labeling
Natural language interfaces
natural language processing
Psychiatrists
Social networks
South Korea
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Summary:Depression disorder is a disease that causes a deterioration of daily function and can induce thoughts of suicide. The Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5), which is the official reference of the American Psychiatry Association and is also used in Korea to identify depressive disorders, sets nine criteria for diagnosing depressive disorders. The lack of counseling personnel, including psychiatrists, and negative social perceptions of depressive disorders prevent counselors from being treated for depressive disorders. Natural language processing-based artificial intelligence (AI) services such as chatbots can help fill this need, but labeled datasets are needed to train AI services. In this study we collected data from AI Hub wellness consultations and crawls of the Reddit website to augment and build word dictionaries and analyze morphemes using the Kind Korean Morpheme Analyzer and Word2Vec. The collected datasets were labeled based on word dictionaries built according to nine DSM-5 depressive disorder diagnostic criteria.
ISSN:2076-3417
2076-3417
DOI:10.3390/app131810481