Classification of mental illness from user content on social media
Author:
Publisher
AIP Publishing
Link
http://aip.scitation.org/doi/pdf/10.1063/5.0103802
Reference13 articles.
1. A.B.R. Shatte, D.M. Hutchinson, and S.J. Teauge, “Machine learning in mental health: A scoping review of methods and applications,” Psychological Medicine. 2019.
2. R. Thorstad and P.Wolff,“Predicting future mental illness from social media :A big-data approach,” Behav,Res.Methods, 2019.
3. J. Dabbs, D.M. Crow, M.R. Mehl, J . W . Pennebaker, and J . H. Price, “The Electronically Activated Recorder (EAR): A device for sampling naturalistic daily activites and conversation,” Behav. Res. Methods, Instruments, Comput., vol 33, no.4,pp.517–523, 2011.
4. H. A. Schwartz et al., “Workshop on Computational Linguistics and Clinical Psychology :From Lingustic Signal Towards Assessing Changes in Degree Of Depression Through Facebook” 2014.
5. P. Resnik et al., “Beyond LDA: Exoploring Supervised Topic Modeling for Depression-Related Language in Twitter,” Vol. 1, No. 2014, pp. 99–107, 2015.
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