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

Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1552) Machine Learning (1491) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1660) Methods and New Tools in Mental Health Research (461) Infodemiology and Infoveillance (1365) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1049)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41823, first published .
Sensing Psychological Well-being Using Social Media Language: Prediction Model Development Study

Sensing Psychological Well-being Using Social Media Language: Prediction Model Development Study

Sensing Psychological Well-being Using Social Media Language: Prediction Model Development Study

Authors of this article:

Nuo Han1, 2, 3 Author Orcid Image ;   Sijia Li4 Author Orcid Image ;   Feng Huang1, 2 Author Orcid Image ;   Yeye Wen5 Author Orcid Image ;   Xiaoyang Wang1 Author Orcid Image ;   Xiaoqian Liu1 Author Orcid Image ;   Linyan Li3, 6 Author Orcid Image ;   Tingshao Zhu1, 2 Author Orcid Image
Article Authors Cited by (3) Tweetations (10) Metrics

Journals

  1. Hou H, Liu I, Kong F, Ni S. Computational positive psychology: advancing the science of wellbeing in the digital era. The Journal of Positive Psychology 2024:1 View
  2. Han N, Wen Y, Wang B, Huang F, Liu X, Li L, Zhu T. Developing a machine learning‐based instrument for subjective well‐being assessment on Weibo and its psychological significance: An evaluative and interpretive research. Applied Psychology: Health and Well-Being 2024;16(4):2246 View