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

Authors

  • Juan Arturo Pérez-Cebreros Instituto Politécnico Nacional
  • Eduardo Vázquez-Fernandez Instituto Politécnico Nacional
  • Alma Partida-Herrera Instituto Politécnico Nacional
  • Geovani Peña-Ramirez Instituto Politécnico Nacional

DOI:

https://doi.org/10.13053/cys-26-1-4177

Keywords:

Social networks, depression, machine learning

Abstract

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.

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Published

2022-03-26

Issue

Vol. 26 No. 1 (2022): Recent Advances in Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez, D. Vilariño)

Section

Articles of the Thematic Issue

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