SetembroBR: a social media corpus for depression and anxiety disorder prediction.

The present work introduces a novel dataset—hereby called the SetembroBR corpus—for the study and development of depression and anxiety disorder predictive models in the Portuguese language based on the information prior to a diagnosis. The corpus comprises both text- and network-related information...

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Detalles Bibliográficos
Publicado en:Language Resources & Evaluation Vol. 58; no. 1; pp. 273 - 301
Autores principales: Santos, Wesley Ramos dos, de Oliveira, Rafael Lage, Paraboni, Ivandré
Formato: Artículo
Publicado: Springer Nature Mar2024
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Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:The present work introduces a novel dataset—hereby called the SetembroBR corpus—for the study and development of depression and anxiety disorder predictive models in the Portuguese language based on the information prior to a diagnosis. The corpus comprises both text- and network-related information related to 3.9 thousand Twitter users who self-reported a diagnosis or treatment for a mental disorder, and its use is illustrated by a number of experiments addressing the issues of depression and anxiety disorder prediction from social media data. Our present results are intended as a first step towards investigating how mental health statuses are expressed on Portuguese-speaking social media, and pave the way for computational applications intended to assist with a pressing issue of great social interest.