Detecting Suicide Risk Through Twitter

Mental illness is one of the main causes of illness worldwide. Currently, it is estimated that about 300 million people suffer from depression according to the World Health Organization (WHO). In this context, this work deals with the construction of a platform that allows to detect the risk of suicide using data from Twitter. This platform combines external emotional processing systems, clustering techniques and a system based on machine learning that facilitate the automatic classification of the information obtained. The entire process is articulated around a multidisciplinary team of professionals in Health Sciences and Information Technology, generating as a result a useful prototype for suicide prevention