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This is perhaps my most polemic blog post yet. Between 1973 and 1989, 1,093 Chileans were forcibly disappeared by the state. This post aims to shed light on this dark chapter of history.

For people that read this blog outside Chile, on September 11th, we commemorate the victims of the dictatorship. It started with the military coup in 1973, which led to widespread human rights violations, including forced disappearances.

Being a member of the R community, I am extremely glad to be a member of a community that puts emphasis on the “be kind to each other” principle. Before September 11th, 1973, it is true that the Socialist government led by President Salvador Allende conducted a dismal economic policy that led to hyperinflation and shortages of basic goods, facts that do not justify the subsequent human rights violations.

I wanted to make this post about Social Media scraping and what people comment 52 years after these events. What I found online was a direct negation of the Golden Rule: “That which is hateful to you, do not do to your neighbor”. I found numerous comments that either justified the actions of the dictatorship or downplayed the severity of the human rights violations.

The coup started with an Air Force raid that destroyed the Government Palace in Santiago de Chile.

After the coup, the Military Junta led by General Augusto Pinochet changed the circulating coins with coins with “Liberty” inscribed on them, a stark contrast to what happened if we consider that liberty is “absence of (arbitrary) coercion”.

I downloaded the data from the Museo de la Memoria y los Derechos Humanos, which includes information about the victims of forced disappearances during the dictatorship.

library(readxl)
library(janitor)
library(dplyr)
library(lubridate)
library(stringr)
library(ggplot2)

url <- "https://interactivos.museodelamemoria.cl/victims/?page_id=7670&exportar_entradas_dd=true"
file <- "2025/09/11/desaparecidos.xlsx"

if (!file.exists(file)) {
  download.file(url, destfile = file, mode = "wb")
}

Then I tidied up the data to create two plots:

1. Year of Arrest and Disappearance
2. Age of Arrest and Disappearance

desaparecidos <- read_excel(file) %>%
    clean_names()

arrest_year <- desaparecidos %>%
    select(fecha_detencion_muerte) %>%
    mutate(year = as.integer(str_sub(fecha_detencion_muerte, -4, -1)))

arrest_year %>%
    filter(is.na(year))

arrest_year <- arrest_year %>%
    group_by(year) %>%
    count()

desaparecidos %>%
    distinct(edad)

arrest_age <- desaparecidos %>%
    select(edad) %>%
    mutate(
        age = case_when(
            str_detect(edad, "meses") ~ "1 - Less than 1",
            edad <= 18 ~ "2 - 18 of less",
            edad > 18 & edad <= 30 ~ "3 - 19 - 30",
            edad > 30 & edad <= 50 ~ "4 - 31 - 50",
            edad > 50 & edad <= 70 ~ "5 - 51 - 70",
            edad > 70 ~ "6 - 71 or more",
            TRUE ~ "7 - Unknown"
        )
    ) %>%
    group_by(age) %>%
    count()

The first plot shows the number of arrests and disappearances by year:

ggplot(arrest_year, aes(x = year, y = n)) +
    geom_col(fill = "#c95555") +
    labs(
        title = "Year of Arrest and Disappearance",
        subtitle = "Source: Museo de la Memoria y los Derechos Humanos",
        x = "Year",
        y = "Number of Arrests"
    ) +
    theme_minimal(base_size = 13)

The second plot shows the age distribution of arrests and disappearances:

ggplot(arrest_age, aes(x = age, y = n)) +
    geom_col(fill = "#c95555") +
    labs(
        title = "Age of Arrest and Disappearance",
        subtitle = "Source: Museo de la Memoria y los Derechos Humanos",
        x = "Age Group",
        y = "Number of Arrests"
    ) +
    theme_minimal(base_size = 13) +
    theme(axis.text.x = element_text(angle = 30, hjust = 1))

The one case of the disappeared infant was not a typo. An eight-month-old baby was forcibly disappeared with her family.

The dataset and code for this post are available on GitHub with information about the age, occupation, political party (if any) and year of arrest or disappearance.