This paper is in the following e-collection/theme issue:

Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Depression and Mood Disorders; Suicide Prevention (1363) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041)

Published on in Vol 20, No 5 (2018): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9267, first published .
Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates

Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates

Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates

Authors of this article:

Elizabeth M Seabrook1 Author Orcid Image ;   Margaret L Kern2 Author Orcid Image ;   Ben D Fulcher1 Author Orcid Image ;   Nikki S Rickard1, 2 Author Orcid Image
Article Authors Cited by (69) Tweetations (22) Metrics

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