In:
Health Informatics Journal, SAGE Publications, Vol. 26, No. 2 ( 2020-06), p. 803-815
Kurzfassung:
Many patients with mental disorders take dietary supplement, but their use patterns remain unclear. In this study, we developed a method to detect signals of associations between dietary supplement intake and mental disorder in Twitter data. We developed an annotated dataset and trained a convolutional neural network classifier that can identify language use pattern of dietary supplement intake with an F1-score of 0.899, a precision of 0.900, and a recall of 0.900. Using the classifier, we discovered that melatonin and vitamin D were the most commonly used supplements among Twitter users who self-diagnosed mental disorders. Sentiment analysis using Linguistic Inquiry and Word Count has shown that among Twitter users who posted mental disorder self-diagnosis, users who indicated supplement intake are more active and express more negative emotions and fewer positive emotions than those who have not mentioned supplement intake.
Materialart:
Online-Ressource
ISSN:
1460-4582
,
1741-2811
DOI:
10.1177/1460458219867231
Sprache:
Englisch
Verlag:
SAGE Publications
Publikationsdatum:
2020
ZDB Id:
2070802-6