Cargando…
Extending A Chronological and Geographical Analysis of Personal Reports of COVID-19 on Twitter to England, UK
The rapidly evolving COVID-19 pandemic presents challenges for actively monitoring its transmission. In this study, we extend a social media mining approach used in the US to automatically identify personal reports of COVID-19 on Twitter in England, UK. The findings indicate that natural language pr...
Autores principales: | Golder, S, Klein, Ari Z., Magge, Arjun, O’Connor, Karen, Cai, Haitao, Weissenbacher, Davy, Gonzalez-Hernandez, Graciela |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273260/ https://www.ncbi.nlm.nih.gov/pubmed/32511492 http://dx.doi.org/10.1101/2020.05.05.20083436 |
Ejemplares similares
-
A chronological and geographical analysis of personal reports of COVID-19 on
Twitter from the UK
por: Golder, Su, et al.
Publicado: (2022) -
A Chronological and Geographical Analysis of Personal Reports of COVID-19 on Twitter
por: Klein, Ari Z., et al.
Publicado: (2020) -
Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set
por: Klein, Ari Z, et al.
Publicado: (2021) -
Deep neural networks ensemble for detecting medication mentions in tweets
por: Weissenbacher, Davy, et al.
Publicado: (2019) -
Automatically Identifying Twitter Users for Interventions to Support Dementia Family Caregivers: Annotated Data Set and Benchmark Classification Models
por: Klein, Ari Z, et al.
Publicado: (2022)