Cargando…
Text Mining Approaches to Analyze Public Sentiment Changes Regarding COVID-19 Vaccines on Social Media in Korea
The COVID-19 pandemic has affected the entire world, resulting in a tremendous change to people’s lifestyles. We investigated the Korean public response to COVID-19 vaccines on social media from 23 February 2021 to 22 March 2021. We collected tweets related to COVID-19 vaccines using the Korean word...
Autores principales: | Shim, Jae-Geum, Ryu, Kyoung-Ho, Lee, Sung Hyun, Cho, Eun-Ah, Lee, Yoon Ju, Ahn, Jin Hee |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296514/ https://www.ncbi.nlm.nih.gov/pubmed/34207016 http://dx.doi.org/10.3390/ijerph18126549 |
Ejemplares similares
-
Sentiment Analysis of Texts on Public Health Emergencies Based on Social Media Data Mining
por: Hu, Nan
Publicado: (2022) -
Sentimental text mining based on an additional features method for text classification
por: Cheng, Ching-Hsue, et al.
Publicado: (2019) -
Analyzing the public sentiment on COVID-19 vaccination in social media: Bangladesh context
por: Zulfiker, Md. Sabab, et al.
Publicado: (2022) -
Analyzing public sentiment toward GMOs via social media between 2019-2021
por: Sohi, Manreet, et al.
Publicado: (2023) -
Public sentiment and opinion regarding the CARES Act
por: Singh, Maliha
Publicado: (2022)