epitweetr (version 2.2.16)

update_languages: 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())

Value

The list of tasks updated with produced messages

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.

See Also

download_dependencies

update_geonames

detect_loop

get_tasks

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()
}