Detecting Suicidal Ideation on Tweets

Abstract

According to the World Health Organization, every 40s a person dies of suicide in the world. Among young people aged 15 to 29, suicide is the second largest cause of death. Yet such deaths can be prevented. In this scenario, social networks like Twitter can become sources of information in real time and help in suicide prevention. The present work makes an initial exploration of the problem of identifying individuals at risk of suicide in social networks in Portuguese Language. As a main result, a manually labeled dataset of tweets has been constructed that can be used in future research on the subject.