Abstract. Automatically detect suicidal people in social networks is a real social issue. In France, suicide attempt is an economic burden with strong socio-economic consequences. In this paper, we describe a complete process to automatically collect suspects tweets according to a vocabulary of topics suicidal persons are used to talk. We automatically capture tweets indicating suicidal risky behaviour based on simple classification methods. An interface for psychiatrists has been implemented to enable them to consults suspect tweets and profiles associated with these tweets. The method has been validated on real datasets. The early feedbacks of psychiatrists are encouraging and allow to consider a personalised response according to the estimated level of risk.
An approach using a vocabulary of topics which suicidal persons are used to talking is presented in REF .
Mining Twitter for Suicide Prevention
NLDB
Computer Science