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Metodología de Análisis de Emociones para Identificar Riesgo de Cometer Suicidio Generado por el COVID-19

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dc.contributor.authorRodríguez Esparza, Luz Judith
dc.contributor.authorBarraza Barraza, Diana
dc.contributor.authorSalazar Ibarra, Jesús
dc.contributor.authorVargas Pasaye, Rafael G.
dc.date.accessioned2022-01-18T14:56:27Z
dc.date.available2022-01-18T14:56:27Z
dc.date.issued2021
dc.description.abstractThe beginning of 2020 was accompanied by a pandemic caused by the virus called SARS-CoV-2. With social distancing measures implemented to prevent the spread of this virus, mental health problems arose, such as anxiety, depression, etc., resulting in a need for telemedicine. Given the alarming numbers of suicide incidences in today’s society, coupled with these distancing measures, support tools are required to identify individuals at risk of committing suicide. Objective: To propose and evaluate a new methodology to calculate suicide risk in Twitter users, based on the analysis of emotions. Materials andMethods: Using statistical learning models (supervised and unsupervised), the proposed methodology identifies the level of risk in the analyzed text of 77 tweets from regular users and political figures in Mexico and Latin America. Results: It was found that, when comparing the methods used, the percentage of coincidence in classification is close to 96%, being the supervised non-parametric and unsupervised methods those that detected the extreme levels of suicide risk. Conclusions: the proposed methodology is a tool that can be of great support for specialists in the mental health area by helping to identify, in a massive way, the presence of signs of mental illness, for its subsequent diagnosis.es_ES
dc.identifier.citationRevista Lasallista de Investigación-Vol. 18 No. 2es_ES
dc.identifier.issn1794-4449
dc.identifier.urihttp://hdl.handle.net/10567/3222
dc.language.isoeses_ES
dc.publisherUnilasallista Corporación Universitaria, Editorial Lasallistaes_ES
dc.rightsAcceso abierto
dc.rights.accessrightsinfo:eu-repo/semantics/openAcces
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/
dc.subjectUnilasallista Corporación Universitariaes_ES
dc.titleMetodología de Análisis de Emociones para Identificar Riesgo de Cometer Suicidio Generado por el COVID-19es_ES

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Revista LASALLISTA de Investigación