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Computación y Sistemas
versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546
Resumen
PEREZ CEBREROS, Juan Arturo; VAZQUEZ FERNANDEZ, Eduardo; PARTIDA HERRERA, Alma y PENA RAMIREZ, Geovani. SVM Based Learning System for the Detection of Depression in Social Networks. Comp. y Sist. [online]. 2022, vol.26, n.1, pp.337-345. Epub 08-Ago-2022. ISSN 2007-9737. https://doi.org/10.13053/cys-26-1-4177.
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.
Palabras llave : Social networks; depression; machine learning.