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Linguistic Features of Suicide Bereavement: A Data Mining Approach
Grace Mei Yi Ooi1, Kai Qin Chan1, Avantika Bhatia2
1College of Healthcare Sciences, James Cook University, Singapore, Singapore.
Omega
|March 3, 2026
Summary
People bereaved by suicide use more cognitive processing and anger words than other grief groups. This language analysis reveals distinct meaning-making and relational grief patterns in suicide loss survivors.
Area of Science:
- Psychology
- Computational Linguistics
- Digital Health
Background:
- Suicide bereavement presents unique challenges, with limited understanding of its linguistic expression and meaning-making processes.
- Online platforms offer naturalistic data for studying grief beyond traditional help-seeking populations.
Purpose of the Study:
- To analyze and compare language use in online suicide bereavement grief expressions versus general bereavement.
- To identify linguistic markers associated with meaning-making and emotional expression in suicide loss survivors.
Main Methods:
- Utilized Linguistic Inquiry and Word Count (LIWC-22) computational text analysis.
- Analyzed 713 posts from the r/SuicideBereavement subreddit and 1149 posts from r/GriefSupport.
- Compared linguistic features between suicide-loss survivors and other bereaved individuals.
Main Results:
- Suicide-loss survivors exhibited increased use of cognitive processing words, indicating deeper meaning-making.
- Survivors showed distinct attentional focus, frequently revisiting the past and the deceased.
- Greater expression of anger, interpersonal conflict, and collective/relational grief language was observed in suicide bereavement.
Conclusions:
- Linguistic analysis reveals distinct cognitive and emotional processing in suicide bereavement.
- Findings advance understanding of suicide loss and inform postvention support strategies.
- Identified linguistic patterns can aid in monitoring and supporting survivors' adjustment.
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