Linguistic Features of Suicide Bereavement: A Data Mining Approach

Suicide bereavement is a uniquely challenging form of loss, yet little is known about how it is expressed in language and how it reflects the meaning-making process. Here, we leveraged naturalistic online language to capture grief expressions beyond traditional help-seeking populations, applying a validated computational text-analysis method (LIWC-22) to 713 posts from the r/SuicideBereavement subreddit and comparing them to 1149 bereavement posts in the r/GriefSupport subreddit. Compared to other bereaved individuals, suicide-loss survivors used more cognitive processing words, reflecting deeper engagement in meaning-making, and displayed distinct attentional focus, frequently revisiting the past and the deceased's life to make sense of the loss. They also expressed greater anger and interpersonal conflict, and used language emphasizing collective and relational aspects of grief. These findings illuminate transdiagnostic processes relevant to bereavement, advancing understanding of suicide loss and suggests new avenues for monitoring and supporting survivors' adjustment in online and community-based postvention contexts.