Early Detection of Public Health Threats from 'Twitter' Data
Plot the top elements for a specific series on the epitweetr dashboard
Plot the top words report on the epitweetr dashboard
Runs the detect loop
Run automatic sanity checks
Plot the map report on the epitweetr dashboard
Snapshot of your epitweetr installation
Updates Java dependencies
algorithm for outbreak detection, extends the EARS algorithm
Run the epitweetr Shiny app
Runs the epitweetr embedded database loop
Execute the alert task
geolocate text in a data frame given a text column and optionally a la...
Getting already aggregated time series produced by detect_loop
Getting signals produced by the task generate_alerts of `detect_loop...
Get the detect_loop task status
Get a sample of latest tweet geolocations (deprecated)
Send email to administrator if a failure of epitweetr is detected
Check whether the alert detection task is running
Check whether the database is running
Check whether the tweet collection task is running
Function used for migrating tweets from to old to the new file system
Registers the alert detection task
Registers the fs_monitor for the current process or exits
Registers the epitweetr database task
Registers the tweet collection task
Save the configuration changes
Runs the search loop
perform full text search on tweets collected with epitweetr
Save Twitter App credentials
Load epitweetr application settings
Stops the alert detection task
Stops the epitweetr database task
Stops the tweet collection task
Plot the trendline report of epitweetr dashboard
Updates the local copy of the GeoNames database
Updates local copies of languages
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. More information is available in the 'epitweetr' peer-review publication (doi:10.2807/1560-7917.ES.2022.27.39.2200177).