Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study.

Baker, William; Colditz, Jason B; Dobbs, Page D; Mai, Huy; Visweswaran, Shyam; Zhan, Justin; Primack, Brian A

Baker, William; Colditz, Jason B; Dobbs, Page D; Mai, Huy; Visweswaran, Shyam; Zhan, Justin; Primack, Brian A.

Afiliación

Baker W; Department of Computer Science and Computer Engineering, University of Arkansas, Fayetteville, AR, United States.
Colditz JB; Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.
Dobbs PD; Health, Human Performance and Recreation Department, University of Arkansas, Fayetteville, AR, United States.
Mai H; Department of Computer Science and Computer Engineering, University of Arkansas, Fayetteville, AR, United States.
Visweswaran S; Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States.
Zhan J; Department of Computer Science and Computer Engineering, University of Arkansas, Fayetteville, AR, United States.
Primack BA; College of Public Health and Human Science, Oregon State University, Corvallis, OR, United States.

JMIR Med Inform ; 10(7): e33678, 2022 Jul 21.

Article en En | MEDLINE | ID: mdl-35862172

Palabras clave

deep learning; infoveillance; social media; transformer models; vaping

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: JMIR Med Inform Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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