SVM based Learning System for the Detection of Depression in Social Networks

Juan Arturo Pérez-Cebreros, Eduardo Vázquez-Fernandez, Alma Partida-Herrera, Geovani Peña-Ramirez


Depression represents a problem of public concern that is now prioritized in many health care agendas with the intention of preventing future suicides, which have devastating impact not only because of tragic loss of life, but also for the grieving family and friends. Investigations in each country reveal a reduction in physical and mental well-being; for this reason the proposal presented in this article comprises an attempt to detect the feelings expressed in text sentences presented in social networks.


Social networks, depression, machine learning

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