| update_languages {epitweetr} | R Documentation | 
Updates local copies of languages
Description
Downloading and indexing a fresh version of language models tagged for update on the Shiny app configuration tab
Usage
update_languages(tasks = get_tasks())
Arguments
tasks | 
 Tasks object for reporting progress and error messages, default: get_tasks()  | 
Details
Run a one shot task to download and index a local fasttext pretrained models. A fasttext model is a collection of vectors for a language automatically produced scrolling a big corpus of text that can be used to capture the semantic of a word.
The URL to download the vectors from are set on the configuration tab of the Shiny app.
This task will also update SVM models to predict whether a word is a location that will be used in the geolocation process.
The indexing is developed in SPARK and Lucene.
A prerequisite to this function is that the search_loop must already have stored collected tweets in the search folder and that the tasks download_dependencies
and update_geonames has been run successfully.
Normally this function is not called directly by the user but from the detect_loop function.
Value
The list of tasks updated with produced messages
See Also
Examples
if(FALSE){
   library(epitweetr)
   # setting up the data folder
   message('Please choose the epitweetr data directory')
   setup_config(file.choose())
   # updating language tasks
   tasks <- update_languages()
}