It allows you to automatically monitor trends of tweets by time, place and topic aiming at detecting public health threats early through the detection of signals (e.g. an unusual increase in the number of tweets). It was designed to focus on infectious diseases, and it can be extended to all hazards or other fields of study by modifying the topics and keywords.
| Version: |
0.1.24 |
| Imports: |
bit64, dplyr, plyr, DT, httpuv, httr, jsonlite, keyring, emayili, ggplot2, magrittr, parallel, plotly, rtweet, readxl, rgeos, rgdal, rmarkdown, rnaturalearthdata, shiny, sp, stringr, stats, tidyverse, tidytext, tokenizers, tools, utils, xtable, xml2 |
| Suggests: |
knitr, taskscheduleR |
| Published: |
2020-10-23 |
| Author: |
Francisco Orchard 
[aut, ctr] (Author of the package and original code),
Laura Espinosa
[aut, cre, fnd] (Project manager, author of the design and concept
of the package, and package maintainer),
Ariana Wijermans [ctb] (Contributor to the design and concept of the
package),
Thomas Mollet [ctb, fnd] (Business owner of the project, and
contributor to the design and concept of the package),
Adrian Prodan [ctb],
Thomas Czernichow [ctb],
Maria Prieto Gonzalez [ctb],
Esther Kissling [ctb],
Michael Höhle [ctb] |
| Maintainer: |
Laura Espinosa <laura.espinosa at ecdc.europa.eu> |
| BugReports: |
https://github.com/EU-ECDC/epitweetr/issues |
| License: |
EUPL |
| URL: |
https://github.com/EU-ECDC/epitweetr |
| NeedsCompilation: |
no |
| CRAN checks: |
epitweetr results |