Cited by 203Mental Health via WritingSuicide and Self-Harm StudiesImpact of Technology on Adolescents

The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.

The Language of Social Support in Social Media and Its Effect on Suicidal Ideation Risk

Open access
De Choudhury, Munmun, Kiciman, Emre·2017·Proceedings of the International AAAI Conference on Web and Social Media

Abstract

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1609/icwsm.v11i1.14891

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 42 references

Research works printed but not linked: 2

  1. Imbens GW Rubin DB 2015 Causal Inference in Statistics, Social, and Biomedical Sciences Cambridge University Press
  2. Rubin DB 2011 Causal inference using potential outcomes Journal of the American Statistical Association

Cited by

Sorted by citations

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
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
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 ›

Are you an author, or do you see a problem with this page? Request a review