Cargando…
Deciphering Latent Health Information in Social Media Using a Mixed-Methods Design
Natural language processing techniques have increased the volume and variety of text data that can be analyzed. The aim of this study was to identify the positive and negative topical sentiments among diet, diabetes, exercise, and obesity tweets. Using a sequential explanatory mixed-method design fo...
Autores principales: | Shaw, George, Zimmerman, Margaret, Vasquez-Huot, Ligia, Karami, Amir |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9691243/ https://www.ncbi.nlm.nih.gov/pubmed/36421644 http://dx.doi.org/10.3390/healthcare10112320 |
Ejemplares similares
-
Targeted advertisement of chlamydia screening on social media: A mixed-methods analysis
por: Nadarzynski, Tom, et al.
Publicado: (2019) -
Analysis of Social Media Discussions on (#)Diet by Blue, Red, and Swing States in the U.S.
por: Karami, Amir, et al.
Publicado: (2021) -
Latent human traits in the language of social media: An open-vocabulary approach
por: Kulkarni, Vivek, et al.
Publicado: (2018) -
Cervical Myelopathy and Social Media: Mixed Methods Analysis
por: Elkaim, Lior M, et al.
Publicado: (2023) -
BSocial: Deciphering Social Behaviors within Mixed Microbial Populations
por: Purswani, Jessica, et al.
Publicado: (2017)