Early Detection of Public Health Threats from Twitter Data

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.


Reference manual

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0.1.24 by Laura Espinosa, 3 months ago


Report a bug at https://github.com/EU-ECDC/epitweetr/issues

Browse source code at https://github.com/cran/epitweetr

Authors: 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]

Documentation:   PDF Manual  

EUPL license

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

See at CRAN