Publicación: Generation of social network user profiles and their relationship with suicidal behaviour
Cargando...
Fecha
2024
Editor/a
Director/a
Tutor/a
Coordinador/a
Prologuista
Revisor/a
Ilustrador/a
Derechos de acceso
Atribución-NoComercial-SinDerivadas 4.0 Internacional
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
Título de la revista
ISSN de la revista
Título del volumen
Editor
Sociedad Española para el Procesamiento del Lenguaje Natural
Resumen
Actualmente el suicidio es una de las principales causas de muerte en el mundo, por lo que poder caracterizar a personas con esta tendencia puede ayudar a prevenir posibles intentos de suicidio. En este trabajo se ha recopilado un corpus, llamado SuicidAttempt en español compuesto por usuarios con o sin menciones explícitas de intentos de suicidio, usando la aplicación de mensajería Telegram. Para cada uno de los usuarios se han anotado distintos rasgos demográficos de manera semi-automática mediante el empleo de distintos sistemas, en unos casos supervisados y en otros no supervisados. Por último se han analizado estos rasgos recogidos, junto con otros lingüísticos extraídos de los mensajes de los usuarios, para intentar caracterizar distintos grupos en base a su relación con el comportamiento suicida. Los resultados sugieren que la detección de estos rasgos demográficos y psicolingüísticos permiten caracterizar determinados grupos de riesgo y conocer en profundidad los perfiles que realizan dichos actos.
Suicide is one of the leading causes of death worldwide, so characterising individuals with such tendencies can help prevent suicide attempts. In this study, a corpus, called SuicidAttempt, of Telegram messaging app users, both with and without explicit mentions of suicide attempts, has been compiled in Spanish. For each user, different demographic features were semi-automatically annotated by different systems, some supervised and some unsupervised. Finally, the collected features and linguistic features extracted from users’ messages were analysed to characterise different groups based on their relationship with suicidal behaviour. The results indicate that by detecting these demographic and psycholinguistic features, it is possible to characterise specific at-risk groups and gain detailed insight into the profiles of those who engage in such acts.
Suicide is one of the leading causes of death worldwide, so characterising individuals with such tendencies can help prevent suicide attempts. In this study, a corpus, called SuicidAttempt, of Telegram messaging app users, both with and without explicit mentions of suicide attempts, has been compiled in Spanish. For each user, different demographic features were semi-automatically annotated by different systems, some supervised and some unsupervised. Finally, the collected features and linguistic features extracted from users’ messages were analysed to characterise different groups based on their relationship with suicidal behaviour. The results indicate that by detecting these demographic and psycholinguistic features, it is possible to characterise specific at-risk groups and gain detailed insight into the profiles of those who engage in such acts.
Descripción
Categorías UNESCO
Palabras clave
comportamiento suicida, identificación de perfiles, creación de corpus, redes sociales, Suicidal behaviour, profiling, corpus creation, social networks
Citación
Centro
E.T.S. de Ingeniería Informática
Departamento
Lenguajes y Sistemas Informáticos