The goal of freedomhouse is to ease the usage of the Freedom in the World dataset from Freedom House in R. The Freedom in the World dataset is updated annually and is originally available for download in Excel format.
Freedom House is best known for political advocacy surrounding issues of Democracy, Political Freedom, and Human Rights. Each of these issues trascends political colours. The Freedom in the World dataset is a comprehensive and widely used measure of political freedom. It is used by academics, journalists, and policy makers alike.
My added value is to presents all the tables in a really simple to use format and to make all the texts with the justifications for each sub-item scores, that you find in around 1,000 links of the form https://freedomhouse.org/country/canada/freedom-world/2023, available in a single tidy table. This is useful for text mining and sentiment analysis.
Another addition of mine was is to add translations.
You can install the development version of freedom from GitHub with:
# install.packages("remotes")
remotes::install_github("pachadotdev/freedomhouse")To install a translation, such as the Spanish translation, you can use:
remotes::install_github("pachadotdev/freedomhouse", subdir = "translations/es")This is a basic example which shows you how to use the available three tables.
library(dplyr)
library(freedomhouse)
# Search Canada in 2023
country_rating_status %>%
filter(country == "Canada", year == 2023)
#> # A tibble: 1 × 9
#> year country iso2c iso3c continent political_rights civil_liberties status
#> <int> <fct> <fct> <fct> <fct> <int> <int> <fct>
#> 1 2023 Canada CA CAN Americas 1 1 Free
#> # ℹ 1 more variable: color <fct>
# Search for the "trade union" sub item score for Canada
country_score %>%
filter(country == "Canada", year == 2023) %>%
filter(grepl("trade union", sub_item_description)) %>%
select(sub_item_description)
#> # A tibble: 1 × 1
#> sub_item_description
#> <fct>
#> 1 Is there freedom for trade unions and similar professional or labor organizat…
# Get the full description of the "trade union" sub-item
country_score %>%
filter(sub_item == "E3") %>%
distinct(sub_item_description)
#> # A tibble: 1 × 1
#> sub_item_description
#> <fct>
#> 1 Is there freedom for trade unions and similar professional or labor organizat…
# Get the justification for the score on sub item E3
country_rating_text %>%
filter(
iso3c == "CAN",
year == 2023,
sub_item == "E3"
) %>%
pull(detail)
#> [1] Trade unions and business associations enjoy high levels of membership and are well organized.
#> 27551 Levels: Afghanistan's political rights rating improved from 6 to 5 due to increased opposition political activity ahead of scheduled elections, as well as modest gains in government transparency. ...There is an example with Shiny here.
The directory dev/texts contains the Excel files that I used for the
translations in dev/texts/translation_es. These can be used as
templates for translations to other languages different from Spanish.
What I did to add the translations in R was to use the left_join
function from the dplyr package to match each country/item/sub-item
with the corresponding translation.
Replica del ejemplo anterior.
# remotes::install_github("pachadotdev/freedomhouse", subdir = "translations/es")
library(dplyr)
library(freedomhouse)
estado_calificacion_pais %>%
filter(pais == "Canadá", anio == 2023)
# # A tibble: 1 × 9
# anio pais iso2c iso3c continente derechos_politicos libertades_civiles
# <int> <fct> <fct> <fct> <fct> <int> <int>
# 1 2023 Canadá CA CAN Américas 1 1
# # ℹ 2 more variables: estado <fct>, color <fct>
puntaje_pais %>%
filter(pais == "Canadá", anio == 2023) %>%
filter(grepl("sindicato", descripcion_sub_categoria)) %>%
select(sub_categoria)
# # A tibble: 1 × 1
# sub_categoria
# <chr>
# 1 E3
puntaje_pais %>%
filter(sub_categoria == "E3") %>%
distinct(descripcion_sub_categoria)
# # A tibble: 1 × 1
# descripcion_sub_categoria
# <chr>
# 1 ¿Existe libertad para los sindicatos y organizaciones profesionales o laboral…
# Get the justification for the score on sub item E3
texto_calificacion_pais %>%
filter(
iso3c == "CAN",
anio == 2023,
sub_categoria == "E3"
) %>%
pull(detalle)
# [1] Los sindicatos y las asociaciones empresariales gozan de un alto nivel de afiliación y están bien organizados.
# 27269 Levels: La calificación de derechos políticos de Afganistán mejoró de 6 a 5 debido a una mayor actividad política de la oposición antes de las elecciones programadas, así como a modestos avances en la transparencia del gobierno. ...To verify the changes made to the package, run the following commands:
devtools::document()
attachment::att_amend_desc()
devtools::check()