BMI trajectory and inflammatory effects on metabolic syndrome in adolescents

Author(s)

dos Santos, Wesley Ramos ; de Oliveira, Rafael Lage ; Paraboni, Ivandre

• Document type: Journal article
• Source: Language Resources and Evaluation; v. N/A, p. 28-pg., 2023-01-11.

Abstract

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. (AU)

• FAPESP's process: 19/07665-4 - Center for Artificial Intelligence
• Grantee: Fabio Gagliardi Cozman
• Support Opportunities: Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program
• FAPESP's process: 21/08213-0 - Social media language analysis for early detection of mental health disorders
• Grantee: Ivandre Paraboni
• Support Opportunities: Regular Research Grants