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The Language of Social Support in Social Media and Its Effect on Suicidal Ideation Risk
Open accessAbstract
Online social support is known to play a significant role in mental well-being. However, current research is limited in its ability to quantify this link. Challenges exist due to the paucity of longitudinal, pre- and post mental illness risk data, and reliable methods that can examine causality between past availability of support and future risk. In this paper, we propose a method to measure how the language of comments in Reddit mental health communities influences risk to suicidal ideation in the future. Incorporating human assessments in a stratified propensity score analysis based framework, we identify comparable subpopulations of individuals and measure the effect of online social support language. We interpret these linguistic cues with an established theoretical model of social support, and find that esteem and network support play a more prominent role in reducing forthcoming risk. We discuss the implications of our work for designing tools that can improve support provisions in online communities.
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“The fourth method involved comparing our temporal trends (treatment), speci fi c to the schools and their respective drill dates, with a suitably chosen control time series in the same timeframe (De Choudhury and Kiciman, 2017).”
From Impacts of school shooter drills on the psychological well-being of American K-12 school communities: a social media study (2021) · cites this paper as De Choudhury and Kiciman, 2017
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“In the context of suicide, certain types of social support in Reddit communities may reduce the chances of future suicidal ideation among those seeking mental health help [61].”
From Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media (2020) · cites this paper as [61]
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Shimgekar, S. R., Zhao, R., Goyal, A., Rodriguez, V. J., Bloom, P. A., Kumar, N., Sundaram, H., & Saha, K. (2026) · ACM Web Science Conference (WebSci) · doi:10.1145/3795766.3799758 · Cited by 4
Suicide Risk Prediction via Comment-Influenced Mental State Trajectories
Li, J., Wang, X., Zhang, Z., Zhao, Q., Leong, H., & Li, Q. (2026) · International World Wide Web Conference (WWW) · doi:10.1145/3774905.3795450
Metadata
- Authors
- De Choudhury, M., & Kiciman, E.
- Venue
- Proceedings of the International AAAI Conference on Web and Social Media
- Published
- 2017-05-03
- Volume
- 11
- Issue
- 1
- Pages
- 32-41
- ISSN
- 2162-3449 (ISSN-L)
- 2334-0770
- PMC
- PMC5565730
- OpenAlex
- W2596823239
- Cited by
- 202
- References
- 42
- Citations by year
- 2026: 15 · 2025: 17 · 2024: 21 · 2023: 25 · 2022: 24 · 2021: 34 · 2020: 27 · 2019: 19 · 2018: 14 · 2017: 6
- FWCI
- 29.26
- Type
- conference paper
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Proceedings of the International AAAI Conference on Web and Social Media (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) (submittedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM112697)
- Topics
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Social Sciences › Psychology › Clinical Psychology › Suicide and Self-Harm Studies
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Keywords
- online social support, suicidal ideation, social media comments, linguistic analysis, mental illness risk, esteem, network support, online community design
About these checks
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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