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()
}