Crisis
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Suicide is a leading cause of death worldwide. Identifying those at risk and delivering timely interventions is challenging. Social media site Twitter is used to express suicidality. Automated linguistic analysis of suicide-related posts may help to differentiate those who require support or intervention from those who do not. ⋯ This study demonstrates that strongly concerning suicide-related Twitter posts have unique linguistic profiles. The examination of Twitter data for the presence of such features may help to validate online risk assessments and determine those in need of further support or intervention.