Detecting depression and mental illness on social media: an integrative review
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The lack of consent or awareness is especially crucial when the data relates to a socially stigmatizing health condition such as mental illness.
“For instance, data is typically captured from social media platforms without the consent or awareness of users (Bidargaddi et al., 2017), which is especially crucial when the data relates to a socially stigmatizing health condition such as mental illness (Guntuku, Yaden, Kern, Ungar, & Eichstaedt, 2017).”
From Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice (2020) · cites this paper as Guntuku, Yaden, Kern, Ungar, & Eichstaedt, 2017
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“Depression continues to be under-diagnosed, with roughly half the cases detected by primary care physicians [1] and only 13–49% receiving minimally adequate treatment [2].”
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Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice
Naslund, J. A., Bondre, A., Torous, J., & Aschbrenner, K. A. (2020) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-020-00134-x · Cited by 746 · see citing works
Methods in predictive techniques for mental health status on social media: a critical review
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- Authors
- Guntuku, S. C., Yaden, D. B., Kern, M. L., Ungar, L. H., & Eichstaedt, J. C.
- Affiliations
- University of Pennsylvania (US)
- The University of Melbourne (AU)
- Corresponding author
- Eichstaedt, Johannes C
- Venue
- Current Opinion in Behavioral Sciences
- Publisher
- Elsevier BV
- Published
- 2017-12
- Volume
- 18
- Pages
- 43-49
- ISSN
- 2352-1546 (ISSN-L)
- OpenAlex
- W2741216199
- Cited by
- 722
- References
- 11
- Citations by year
- 2026: 99 · 2025: 85 · 2024: 71 · 2023: 98 · 2022: 81 · 2021: 88 · 2020: 99 · 2019: 56 · 2018: 41 · 2017: 3
- FWCI
- 8.47
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Current Opinion in Behavioral Sciences (publishedVersion)
- Funders
- Templeton Religion Trust (#TRT0048)
- Topics
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Keywords
- depression detection, mental illness, social media, automated detection, Twitter, Facebook, online forums, linguistic patterns, online activities, passive monitoring, mental health screening, at-risk individuals
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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