Access the Polarization in Comparative Attitudes Project • PolarCAP

Welcome to the Polarization in Comparative Attitudes Project (PolarCAP)! This site describes the R package PolarCAP—the main portal to PolarCAP data—and provides access to data files in a variety of formats for users not familiar with R. The short vignettes below explain how to retrieve data using PolarCAP and the links above provide access to function reference manuals, a record of changes to the package, downloadable data files, and the R package CPC, which was used to generate the final PolarCAP estimates. For detailed information on the estimation of PolarCAP data, please see the book manuscript cited at the bottom of this page.

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")

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")

Citation

To cite PolarCAP in publications and working papers, please use:

Mehlhaff, Isaac D. Mass Polarization across Time and Space. New York: Cambridge University Press (forthcoming).

For BibTeX users:

@book{Mehlhaffbook,
  title = {Mass {{Polarization}} across {{Time}} and {{Space}}},
  author = {Mehlhaff, Isaac D.},
  note = {forthcoming},
  publisher = {{Cambridge University Press}},
  location = {{New York}}
}