An Overview of UN Votes over Time

Author

Emily Kurtz

Published

March 30, 2026

Summarizing the dataset

The unvotes R package contains many datasets on votes among UN member nations at General Assembly meetings. In this document, we will merge two of these datasets, un_roll_calls and un_roll_call_issues, summarize some information from this merged dataset, and create a visual that shows a handful of countries’ voting patterns over time. In the merged dataset unvotes, each row represents a country’s vote on some issue domain (e.g. human rights) in a given session. The merged dataset consists of 857878 country-session-issues (i.e. rows) and 14 variables (i.e., columns). There are 200 unique member nations in the dataset. The dataset includes votes from 1946 to 2019.

UN Voting Patterns

Below is a data visualization that displays how the voting records of United Kingdom, United States, and Turkey changed over time from 1946 to 2019.

---
title: "An Overview of UN Votes over Time"
date: "Last updated on `r Sys.Date()`"
author: "Emily Kurtz"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, message = FALSE)
```

```{r}
#| echo: false
#| warning: false
library(tidyverse)
library(lubridate)
library(scales)
library(DT)
library(unvotes)
```

```{r}
#| echo: false
#| warning: false
unvotes <- un_votes %>%
  inner_join(un_roll_calls, by = "rcid") %>%
  inner_join(un_roll_call_issues, by = "rcid")

countrySample <- c("United Kingdom", "United States", "Turkey")
```

## Summarizing the dataset

The `unvotes` R package contains many datasets on votes among UN member nations at General Assembly meetings. In this document, we will merge two of these datasets, un_roll_calls and un_roll_call_issues, summarize some information from this merged dataset, and create a visual that shows a handful of countries' voting patterns over time. In the merged dataset unvotes, each row represents a country's vote on some issue domain (e.g. human rights) in a given session. The merged dataset consists of `r nrow(unvotes)` country-session-issues (i.e. rows) and `r ncol(unvotes)` variables (i.e., columns). There are `r length(unique(unvotes$country))` unique member nations in the dataset. The dataset includes votes from `r min(year(unvotes$date))` to `r max(year(unvotes$date))`.

## UN Voting Patterns

Below is a data visualization that displays how the voting records of `r countrySample[1]`, `r countrySample[2]`, and `r countrySample[3]` changed over time from `r min(year(unvotes$date))` to `r max(year(unvotes$date))`.

```{r plot-yearly-yes-issue, message = FALSE, fig.width=10, fig.height=6}
#| echo: false
#| warning: false
unvotes %>%
  filter(country %in% countrySample) %>%
  mutate(year = year(date)) %>%
  group_by(country, year, issue) %>%
  summarize(percent_yes = mean(vote == "yes")) %>%
  ggplot(mapping = aes(x = year, y = percent_yes, color = country)) +
  geom_point(alpha = 0.4) +
  geom_smooth(method = "loess", se = FALSE) +
  facet_wrap(~issue) +
  labs(
    title = "Percentage of 'Yes' votes in the UN General Assembly",
    subtitle = "1946 to 2019",
    y = "% Yes",
    x = "Year",
    color = "Country"
  )
```