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...
| Publicado en: | Language Resources & Evaluation Vol. 58; no. 1; pp. 273 - 301 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Nature
Mar2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=176079983&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 176079983 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Mar2024 vid: 58 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 176079983 10.1007/s10579-022-09633-0 ppf: 273 ppct: 28 formats: fmt: – @attributes: type: T – @attributes: type: P size: 895KB tig: atl: SetembroBR: a social media corpus for depression and anxiety disorder prediction. aug: au: Santos, Wesley Ramos dos de Oliveira, Rafael Lage Paraboni, Ivandré affil: https://ror.org/036rp1748 School of Arts, Sciences and Humanities (EACH), University of São Paulo (USP), São Paulo, Brazil su: Anxiety disorders Microblogs Social media Natural language processing Portuguese language Mental illness sug: subj: Anxiety disorders Microblogs Social media Natural language processing Portuguese language Mental illness keyword: Anxiety disorder Corpora Depression Portuguese NLP ab: 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. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2024. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2024 holdings: @attributes: islocal: N |
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