Tragically, an estimated 42,000 Americans died by suicide in 2015, each one deeply affecting friends and family. Very little data and information is available about people who attempt to take their life, and thus scientific exploration has been hampered. We examine data from Twitter users who have attempted to take their life and provide an exploratory analysis of patterns in language and emotions around their attempt. We also show differences between those who have attempted to take their life and matched controls. We find quantifiable signals of suicide attempts in the language of social media data and estimate performance of a simple machine learning classifier with these signals as a non-invasive analysis in a screening process.
Through analysis of tweets posted by individuals attempting committing suicide, REF indicate quantifiable signals of suicidal ideations.
Exploratory Analysis of Social Media Prior to a Suicide Attempt
CLPsych@HLT-NAACL
Computer Science