Analysis

Let’s take a look at the voting history of countries in the United Nations General Assembly. We will be using data from the unvotes package. Additionally, we will make use of the tidyverse and lubridate packages for the analysis, and the DT package for interactive display of tabular output.

library(tidyverse)
library(unvotes)
library(lubridate)
library(DT)

The unvotes package provides three datasets we can work with: un_roll_calls, un_roll_call_issues, and un_votes. Each of these datasets contains a variable called rcid, the roll call id, which can be used as a unique identifier to join them with each other.

  • The un_votes dataset provides information on the voting history of the United Nations General Assembly. It contains one row for each country-vote pair.
  • The un_roll_calls dataset contains information on each roll call vote of the United Nations General Assembly.
  • The un_roll_call_issues dataset contains (topic) classifications of roll call votes of the United Nations General Assembly. Many votes had no topic, and some have more than one.

Let’s create a visualization that we create a visualization that displays how the voting record of the United States changed over time on a variety of issues, and compares it to another country. The other country we’ll display is Turkey.

un_votes %>%
  filter(country %in% c("United States of America", "Turkey", "Ireland")) %>%
  inner_join(un_roll_calls, by = "rcid") %>%
  inner_join(un_roll_call_issues, by = "rcid") %>%
  mutate(issue = ifelse(issue == "Nuclear weapons and nuclear material",
                        "Nuclear weapons and materials", issue)) %>%
  group_by(country, year = year(date), issue) %>%
  summarize(
    votes = n(),
    perc_yes = mean(vote == "yes")
    ) %>%
  filter(votes > 5) %>%  # only use records where there are more than 5 votes
  ggplot(mapping = aes(x = year, y = perc_yes, color = country)) +
    geom_point() +
    geom_smooth(method = "loess", se = FALSE) +
    facet_wrap(~ issue) +
    labs(
      title = "Percentage of Yes votes in the UN General Assembly",
      subtitle = "1946 to 2015",
      y = "% Yes",
      x = "Year",
      color = "Country"
    )

We can easily change which countries are being plotted by changing which countries the code above filters for. Note that the country name should be spelled and capitalized exactly the same way as it appears in the data. See the Appendix for a list of the countries in the data.

References

  1. David Robinson (2017). unvotes: United Nations General Assembly Voting Data. R package version 0.2.0. https://CRAN.R-project.org/package=unvotes.
  2. Erik Voeten “Data and Analyses of Voting in the UN General Assembly” Routledge Handbook of International Organization, edited by Bob Reinalda (published May 27, 2013).
  3. Much of the analysis has been modeled on the examples presented in the unvotes package vignette.

Appendix

Below is a list of countries in the dataset: