Access the Polarization in Comparative Attitudes Project.
PolarCAP
Distributes data from the Polarization in Comparative Attitudes Project. Helper functions enable data retrieval in wide and tidy formats for user-defined countries and years. Provides support for case-insensitive country names in many languages.
Installation
There are two ways to easily install this package in R. To install the stable version released to CRAN, install as normal:
install.packages("PolarCAP")
library(PolarCAP)
To install the most recent development version, first ensure you have the latest version of devtools
installed:
install.packages("devtools")
library(devtools)
Then, run the following code:
devtools::install_github("imehlhaff/PolarCAP")
Citation
To cite PolarCAP
in publications and working papers, please use:
Mehlhaff, Isaac D. Mass Polarization across Time and Space, book manuscript (August 2023).
For BibTeX users:
@unpublished{Mehlhaff2023,
type = {Book {{Manuscript}}},
title = {Mass {{Polarization}} across {{Time}} and {{Space}}},
author = {Mehlhaff, Isaac D.},
year = {2023},
month = aug,
address = {{The University of North Carolina at Chapel Hill}}
}
Usage
Most users of this package will be primarily interested in using it to easily retrieve polarization estimates for a defined set of countries and years. For example, let us take the countries and years generated by the following:
countries <- rep(c("AUS", "MEX", "USA"), each = 2)
years <- rep(c(2018, 2019), 3)
data <- as.data.frame(cbind(countries, years))
Retrieve Data Frame
One way to retrieve polarization estimates for the countries and years generated above is to pass the vectors of countries and years to get.PolarCAP()
or melt.PolarCAP()
, which return wide and tidy data frames, respectively:
get.PolarCAP(countries = countries, years = years, type = c("ideology", "affect"))
melt.PolarCAP(countries = countries, years = years, type = c("ideology", "affect"))
Standard errors of polarization estimates can be retrieved by adding the optional include.se
argument, which defaults to FALSE
:
get.PolarCAP(countries = countries, years = years, type = c("ideology", "affect"), include.se = TRUE)
melt.PolarCAP(countries = countries, years = years, type = c("ideology", "affect"), include.se = TRUE)
Retrieve Individual Values
Another way to retrieve polarization estimates for the same set of countries and years is to return only the scalar polarization estimate associated with each country-year. This feature is particularly useful if a user has an imbalanced time series, would prefer to avoid merging data frames, or is working within a dplyr
pipeline:
data$ideology1 <- apply(data, 1, function(x) get.PolarCAP(countries = x[1], years = x[2], type = "ideology", value.only = TRUE))
data <- rowwise(data) %>% mutate(ideology2 = get.PolarCAP(countries = countries, years = years, type = "ideology", value.only = TRUE))
data
A Note on Country Identifiers
The countries defined above are in ISO 3166-1 alpha-3 country code format. This is the preferred input for *.PolarCAP()
. However, these functions will accept country names in almost any language or format and attempt to convert them to ISO3 codes by calling to.ISO3()
. *.PolarCAP()
will alert the user to any country names still unrecognized after this conversion and return results only for those which are recognized. In addition, country codes are case-insensitive. Thus, the following all return the same output:
get.PolarCAP(countries = c("AUS", "MEX", "USA"), years = 2019, type = "ideology")
get.PolarCAP(countries = c("aus", "MEX", "united states"), years = 2019, type = "ideology")
get.PolarCAP(countries = c("aus", "MEX", "Stati Uniti"), years = 2019, type = "ideology")