--- title: "Visualizing Press Freedom Trends" author: "Peter Baumgartner" date: "`r Sys.Date()`" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Visualizing Press Freedom Trends} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r chunk-options, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 5 ) ``` ## Purpose This vignette is a gallery, not an analysis. Its only goal is to show, through a handful of charts, the kinds of questions {pressfreedom.data} makes possible to ask. For instance: - tracking a single country over time, - comparing countries against each other, - breaking a score down into its component dimensions - following global and regional trends. None of the charts below are meant to support a substantive conclusion about press freedom; even if some conclusions are not far to seek. Read these charts as demonstrations of the data's shape and coverage, aimed at researchers deciding whether this dataset is useful for their own work. For a conceptual introduction to the dataset (its columns, time periods, and known data-quality caveats), see vignette("getting-started"). ## Setup The charts in this vignette use {ggplot2} for line/point charts, including rank-crossing ("bump") comparisons, and {tidyr} for reshaping wide dimension columns into a long format for plotting. {dplyr} is used throughout for filtering, grouping, and summarizing. ```{r setup} library(pressfreedom.data) library(dplyr) library(ggplot2) library(tidyr) library(patchwork) library(sf) data(rwb_standardized) ``` **A reminder before plotting:** - `score` is only comparable from 2013 onward -- RSF changed its scoring methodology that year. - `rank` is always comparable across the full 2002-2026 span. It is just a country's position among that year's countries. - The five dimension columns (`political_context`, `economic_context`, `legal_context`, `social_context`, and `safety`) are available from 2022 onward. - The year 2011 is completely missing. RSF.org did not publish data for that year. ## Track a Specific Country `rank` and `score` tell complementary stories for a single country. `rank` is a country's position among that year's countries, so it is comparable across the whole 2002-2026 span. `score` uses RSF's underlying point scale, which is only comparable from 2013 onward. The two charts below show both for the United States, side by side, each starting at the year from which its values are meaningful. ```{r us-setup} us_rank <- rwb_standardized |> filter(country_en == "United States", !is.na(rank)) |> arrange(year_n) us_score <- rwb_standardized |> filter(country_en == "United States", year_n >= 2013, !is.na(score)) |> arrange(year_n) ``` ```{r us-charts, fig.alt = "Two line charts side by side: the United States' press freedom rank from 2002 to 2026 on the left, and its score from 2013 to 2026 on the right."} p_us_rank <- ggplot(us_rank, aes(x = year_n, y = rank)) + geom_line() + geom_point() + scale_y_reverse() + labs(x = "Year", y = "Rank (1 = most free)", title = "Rank, 2002-2026") p_us_score <- ggplot(us_score, aes(x = year_n, y = score)) + geom_line() + geom_point() + labs( x = "Year", y = "Score (100 = most free)", title = "Score, 2013-2026" ) p_us_rank + p_us_score ``` ## Compare Countries Over Time The six countries below -- the United States, China, Brazil, Nigeria, Japan, and Germany -- span a mix of regions and press-freedom trajectories. ```{r compare-setup} compare_countries <- c( "United States", "China", "Brazil", "Nigeria", "Japan", "Germany" ) compare_score <- rwb_standardized |> filter(country_en %in% compare_countries, year_n >= 2013, !is.na(score)) |> arrange(country_en, year_n) compare_rank <- rwb_standardized |> filter(country_en %in% compare_countries, !is.na(rank)) |> arrange(country_en, year_n) ``` ```{r compare-score-chart, fig.alt = "Line chart comparing press freedom scores for the United States, China, Brazil, Nigeria, Japan, and Germany from 2013 to 2026."} # Order the legend to match each country's end-of-series score, top to # bottom, instead of the alphabetical default compare_score <- compare_score |> mutate(country_en = forcats::fct_reorder2(country_en, year_n, score)) ggplot(compare_score, aes(x = year_n, y = score, color = country_en)) + geom_line() + geom_point() + labs( x = "Year", y = "Score (100 = most free)", color = "Country", title = "Press Freedom Score, 2013-2026" ) ``` For rank, a bump chart shows how the six countries' relative positions cross over the full 2002-2026 span, since `rank` does not share `score`'s 2013 comparability limit: ```{r compare-rank-chart, fig.alt = "Bump chart comparing press freedom rank for the United States, China, Brazil, Nigeria, Japan, and Germany from 2002 to 2026, with a reversed y-axis.", fig.height = 6} # `.desc = FALSE` because the y-axis is reversed below (rank 1 = best, drawn # at the top); ordering the legend ascending by rank keeps it in the same # top-to-bottom order as the lines at their right-hand endpoints compare_rank <- compare_rank |> mutate(country_en = forcats::fct_reorder2( country_en, year_n, rank, .desc = FALSE )) ggplot(compare_rank, aes(x = year_n, y = rank, color = country_en)) + geom_line(linewidth = 1) + geom_point(size = 2) + scale_y_reverse() + labs( x = "Year", y = "Rank (1 = most free)", color = "Country", title = "Press Freedom Rank, 2002-2026" ) ``` ## Work with Dimensions (2022+) From 2022 onward, RSF also reports five sub-dimensions (Political, Economic, Legal, Social, Safety) alongside the overall `score`. Reshaping with `tidyr::pivot_longer()` makes it easy to plot them together for one country. ```{r dimensions_setup} us_dims <- rwb_standardized |> filter(country_en == "United States", year_n >= 2022) |> select( year_n, score, political_context, economic_context, legal_context, social_context, safety ) |> tidyr::pivot_longer( cols = -"year_n", names_to = "dimension", values_to = "value" ) ``` ```{r dimensions_chart, fig.alt = "Line chart for the United States' overall score and five sub-dimensions from 2022 to 2026."} # Order the legend to match each dimension's end-of-series value us_dims <- us_dims |> mutate(dimension = forcats::fct_reorder2(dimension, year_n, value)) ggplot(us_dims, aes(x = year_n, y = value, color = dimension)) + geom_line() + geom_point() + labs( x = "Year", y = "Score (higher is better)", color = "Dimension", title = "United States: Overall Score and Sub-Dimensions, 2022-2026" ) ``` ## Regional Trends Averaging `score` by `zone` and `year_n` (restricted to 2013+, since `score` is not comparable before then) shows how regions have diverged. The black line adds the global mean across all countries for reference. ```{r zones_setup} zone_means <- rwb_standardized |> filter(year_n >= 2013, !is.na(zone), !is.na(score)) |> group_by(zone, year_n) |> summarise(mean_score = mean(score), .groups = "drop") global_mean <- rwb_standardized |> filter(year_n >= 2013, !is.na(score)) |> group_by(year_n) |> summarise(mean_score = mean(score), .groups = "drop") ``` ```{r zones_chart, fig.alt = "Line chart of mean press freedom score by geographic zone from 2013 to 2026, with a black line showing the global mean across all countries."} zone_colors <- c( setNames(scales::hue_pal()(dplyr::n_distinct(zone_means$zone)), sort(unique(zone_means$zone))), "Global mean" = "black" ) # Order the legend (via `breaks`) to match each line's end-of-series value, # combining the zones and the global mean into one ranking legend_order <- bind_rows( zone_means |> filter(year_n == max(year_n)) |> select("zone", "mean_score"), global_mean |> filter(year_n == max(year_n)) |> transmute(zone = "Global mean", mean_score) ) |> arrange(desc(mean_score)) |> pull(zone) ggplot(mapping = aes(x = year_n, y = mean_score, color = zone)) + geom_line(data = zone_means) + geom_point(data = zone_means) + geom_line( data = global_mean, aes(color = "Global mean"), linewidth = 1 ) + geom_point(data = global_mean, aes(color = "Global mean")) + scale_color_manual(values = zone_colors, breaks = legend_order) + labs( x = "Year", y = "Mean score", color = "Zone", title = "Mean Press Freedom Score by Region, 2013-2026" ) ``` ## The Six RSF Regions `zone` groups countries into six regions, following RSF's own regional breakdown. These are RSF's groupings, not a universal standard. Note, for instance, that North Africa sits in `Middle East & North Africa` rather than `Africa`. RSF's regions follow political/cultural groupings, not strict continental geography. But nothing stops a researcher from building alternative regions (e.g. by continent, by income group, by EU membership) directly from `country_en` or `iso`. - **Africa -- Sub-Saharan Africa:** Angola, Benin, Botswana, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo-Brazzaville, Cote d'Ivoire, DR Congo, Djibouti, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria, Rwanda, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, Togo, Uganda, Zambia, Zimbabwe. - **Americas -- North, Central, and South America, and the Caribbean:** Argentina, Belize, Bolivia, Brazil, Canada, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, OECS, Panama, Paraguay, Peru, Suriname, Trinidad and Tobago, United States, Uruguay, Venezuela. - **Asia-Pacific -- Asia and the Pacific:** Afghanistan, Australia, Bangladesh, Bhutan, Brunei, Cambodia, China, East Timor, Fiji, Hong Kong, India, Indonesia, Japan, Laos, Malaysia, Maldives, Mongolia, Myanmar, Nepal, New Zealand, North Korea, Pakistan, Papua New Guinea, Philippines, Samoa, Singapore, South Korea, Sri Lanka, Taiwan, Thailand, Tonga, Vietnam. - **Eastern Europe & Central Asia -- Commonwealth of Independent States:** Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkiye, Turkmenistan, Ukraine, Uzbekistan. - **Middle East & North Africa:** Algeria, Bahrain, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Libya, Morocco / Western Sahara, Oman, Palestine, Qatar, Saudi Arabia, Syria, Tunisia, United Arab Emirates, Yemen. - **EU & Balkans -- European Union member states, EFTA countries, the UK, and the Balkans:** Albania, Andorra, Austria, Belgium, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Kosovo, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Montenegro, Netherlands, North Macedonia, Northern Cyprus, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, United Kingdom. ## A World Map of Press Freedom (2025) A choropleth map gives an at-a-glance view of where press freedom stands globally in a single year. World country boundaries come from {rnaturalearth}; joining them to `rwb_standardized` requires a common key, which is `iso` (the package's ISO 3-letter code) against `iso_a3` in the map data. ```{r map_setup} world <- rnaturalearth::ne_countries(scale = "small", returnclass = "sf") |> # Drop Antarctica, keeps the map focused on populated landmass dplyr::filter(.data$continent != "Antarctica") scores_2025 <- rwb_standardized |> filter(year_n == 2025, !is.na(score)) |> select("iso", "score") world_scores <- world |> left_join(scores_2025, by = c("iso_a3" = "iso")) ``` A handful of small territories in the map data (dependencies, disputed territories) do not have a matching row in `rwb_standardized`, since RSF only rates sovereign states; these are shown in grey. ```{r map_chart, fig.alt = "World map colored by press freedom score in 2025, using the Robinson projection. Countries range from dark red (low score, less free) to light yellow (high score, more free); a handful of small territories not rated by RSF are shown in grey.", fig.width = 7, fig.height = 4.6} ggplot(world_scores) + geom_sf(aes(fill = score), color = NA) + scale_fill_viridis_c( option = "rocket", na.value = "grey70", name = "Score (100 = most free)", guide = guide_colorbar( title.position = "top", title.hjust = 0.5, barwidth = unit(120, "pt"), barheight = unit(6, "pt") ) ) + coord_sf( crs = "+proj=robin", # Crop near the poles (Antarctica already dropped) to remove # the empty white space a full-globe Robinson projection leaves # above and below the populated landmass default_crs = sf::st_crs(4326), xlim = c(-180, 180), ylim = c(-60, 85), expand = FALSE ) + theme_void() + theme( plot.title = element_text(hjust = 0.5), legend.position = "bottom", plot.margin = margin(0, 0, 0, 0) ) + labs(title = "Press Freedom Score by Country, 2025") ```