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Verfasst von:Karmen, Christian [VerfasserIn]   i
 Hsiung, Robert [VerfasserIn]   i
 Wetter, Thomas [VerfasserIn]   i
Titel:Screening internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods
Verf.angabe:Christian Karmen, Robert C. Hsiung, Thomas Wetter
E-Jahr:2015
Jahr:20 March 2015
Umfang:10 S.
Fussnoten:Gesehen am 06.07.2017
Titel Quelle:Enthalten in: Computer methods and programs in biomedicine
Ort Quelle:Amsterdam : Elsevier, 1985
Jahr Quelle:2015
Band/Heft Quelle:120(2015), 1, Seite 27-36
ISSN Quelle:1872-7565
Abstract:Depression is a disease that can dramatically lower quality of life. Symptoms of depression can range from temporary sadness to suicide. Embarrassment, shyness, and the stigma of depression are some of the factors preventing people from getting help for their problems. Contemporary social media technologies like Internet forums or micro-blogs give people the opportunity to talk about their feelings in a confidential anonymous environment. However, many participants in such networks may not recognize the severity of their depression and their need for professional help. Our approach is to develop a method that detects symptoms of depression in free text, such as posts in Internet forums, chat rooms and the like. This could help people appreciate the significance of their depression and realize they need to seek help. In this work Natural Language Processing methods are used to break the textual information into its grammatical units. Further analysis involves detection of depression symptoms and their frequency with the help of words known as indicators of depression and their synonyms. Finally, similar to common paper-based depression scales, e.g., the CES-D, that information is incorporated into a single depression score. In this evaluation study, our depressive mood detection system, DepreSD (Depression Symptom Detection), had an average precision of 0.84 (range 0.72-1.0 depending on the specific measure) and an average F measure of 0.79 (range 0.72-0.9).
DOI:doi:10.1016/j.cmpb.2015.03.008
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: http://dx.doi.org/10.1016/j.cmpb.2015.03.008
 Volltext: http://www.sciencedirect.com/science/article/pii/S0169260715000620
 DOI: https://doi.org/10.1016/j.cmpb.2015.03.008
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Automatic screening
 Depression
 Natural Language Processing
 Social Internet communication
K10plus-PPN:1560542799
Verknüpfungen:→ Zeitschrift

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