Data Analysis: Books Banned by the Nazis
Data reveal Hitler waged a culture war against the free press
In this data analysis, we will explore the authors, titles, and locations of books that were banned by the Nazis in 1935 using a data set provided by Berlin’s Open Data initiative. You can access the data set here. It contains 4762 observations on 13 variables, including the authors’ names, titles, location of publisher, and year of publication. To visualize the data, we’ll use the tidytext, wordcloud, treemap, and ggmap packages in R.
Why Is This Relevant Today?
In the era of the American “war” on the media, filter bubbles, and misinformation, we should remain aware of how those in power can control the flow of information to support their political agendas and re-narrate our collective history.
#Cleaning up for display and loading necessary packages
library(tidyverse)
library(tidytext)
library(wordcloud)
library(treemap)
library(ggmap)
df <- read.csv('nazibooks.csv', stringsAsFactors = F)
df <- df%>%
unite('name', authorfirstname, authorlastname, sep=' ' )
df <- df%>%
mutate(firsteditionpublicationyear = as.integer(firsteditionpublicationyear))Goebbels and the Nazi Ideals of Culture
According to the website, this list was drawn up by the Reich Chamber of Culture (Reichskulturkammer), which was the brainchild of Joseph Goebbels, and was passed on to all libraries and bookstores. According to Wikipedia,
[The Reich Chamber of Culture] was meant to gain control over the entire cultural life in Germany creating and promoting Aryan art consistent with Nazi ideals. Every artist had to apply for membership on presentation of an Aryan certificate. A rejected inscription de facto resulted in an occupational ban.
Two Kinds of Banned Books
There were actually two types of ‘flags’ used by the SS: the first type was for books that ‘threatened the Nazi culture’ and the second type was for books that were ‘unsuitable to fall into the hands of youth (children under the age of 18).’ These books also could not be shown in storefront windows or placed in bookstores ‘where the general public could find them.’
df%>%
ggplot(aes(firsteditionpublicationyear, fill=as.factor(ssflag)))+
geom_histogram(alpha=.5)+
theme_minimal()+
labs(fill='Type of Ban', x='Year First Published', y='Count')+
annotate('text',x=1890, y=600, size=3, label = 'Type 1: Die Reichsschrifttumskammer führt eine Liste solcher Bücher und Schriften,\n die das nationalsozialistische Kulturwollen gefährden.\n Die Verbreitung dieser Bücher und Schriften durch \n öffentlich zugängliche Büchereien \nund durch den Buchhandel in jeder Form (Verlag, Ladenbuchhandel,\n Versandbuchhandel, Reisebuchhandel, Leihbüchereien usw.) ist untersagt.
\n Type 2: Die Reichsschrifttumskammer führt eine weitere Liste solcher Bücher und Schriften,\n die zwar nicht in die in § 1 erwähnte Liste aufzunehmen,\n jedoch ungeeignet sind, in die Hände Jugendlicher zu gelangen. Solche Schriften dürfen:
1. nicht in Schaufenstern und allgemein zugänglichen Bücherständen öffentlich\n ausgelegt werden,
2. nicht durch Reisende, Bücherkarrenhändler, Ausstellungshändler und sonstige \nHändler ohne festen Verkaufsraum\n vertrieben werden,
3. nicht an Jugendliche unter 18 Jahren ausgehändigt werden.')
We see most of the books were published in the 1930s, though it looks like the second type of ban (aimed at youth) targeted books published slightly earlier. The books published in pre-1900 were likely related to communism. Karl Marx’s The Communist Manifesto (Manifest der Kommunistischen Partei) was published in 1848 and is the earliest published book shown in the histogram.
Tidytext and Wordclouds of Banned Titles
We will use the tidytext package and a custom German stopword dataframe to filter out most of the grammar words. Then we will use the Wordcloud package to visualize the top 150 words from the banned titles. We will first look at single words, then at bigrams, which tend to give more context.
custom_stops <- bind_rows(data.frame(word = c(as.character(seq(1,100,1)),'nicht', 'kann','na', 'en','le', 'het', 'st', 'aufl','hrsg','unsere','de', 'bd', 'la','sämtliche', 'u', 'schriften', stopwords::stopwords(language = 'german')), lexicon = c('custom')), stop_words)my_pal1 <- rev(c("#FF4040", "#EE3B3B", "#8B2323", "#030303"))
df%>%
unnest_tokens(word, title)%>%
anti_join(custom_stops)%>%
count(word, sort=T)%>%
with(wordcloud(word, n, scale=c(2, .3), color=my_pal1, random.color = F, max.words = 150))
And now bigrams to gain a bit more insight into the context of the words.
df[df == ' '] <- 'unknown'
df%>%
filter(ssflag==1)%>%
mutate(title = iconv(title, 'UTF-8', 'latin1'))%>%
unnest_tokens(word, title, token = 'ngrams', n=2)%>%
separate(word, into=c('word1', 'word2'))%>%
#filter(nchar(word1) > 2)%>%
#filter(nchar(word2) > 2)%>%
filter(str_detect(word1, '[a-zA-Z]'))%>%
filter(str_detect(word2, '[a-zA-Z]'))%>%
filter(!word1 %in% custom_stops$word)%>%
filter(!word2 %in% custom_stops$word)%>%
unite('bigram', word1, word2, sep=' ')%>%
count(bigram, sort=T)%>%
with(wordcloud(bigram, n, scale=c(1.2, .3), color=my_pal1, random.color = F, max.words=100))
The Most Dangerous Ideas
In the bigrams cloud, we notice a lot of attention paid to German poetry. It’s likely the Nazis were trying to appropriate the German cultural icons and use them to support their ideology. We also find lots of references to Communism in Russia and China (the Far East). Finally we see the obsession with controlling family values and youth (young generation). The focus on sexual topics is particularly interesting (erotik, prostitution, sexuelle).
From single words, we can see that many of the banned books focused on topics like:
Love, War, History, Germany, Marriage, Youth, Jews, Soviet Union, Hitler, Women, Revolution, Psychoanalysis, Socialism, and Church, among many more.
Re-Narrating The Past
Based on this, we could infer that the Nazis were trying to control how Germans viewed their own history and the events of the Russian Revolution. At the same time, the Nazis were worried about the role of the family and the institution of marriage-particularly the sexual mores of women at the time. And finally, they were attempting to suppress the free expression of ideas related to Christianity and the church.
All of this supports the familiar historical narrative that the Nazis used censorship of the press to support the party ideology of racial superiority. Any books containing ideas that might make people question the party lines were banned from publication.
Where Were Banned Books Published?
In this graphic, we will look at where banned books were published. In order to do this we will need to geo-code the cities and join them with counts of publications.
#these were created separately
map_counts <- read.csv('euro_map_counts.csv')
nazi_words <- read.csv('top_nazi_words.csv')
#Google maps has changed its API since this time...
w_map <- get_map('Europe', zoom=4, maptype = 'toner')
ggmap(w_map)+
geom_point(aes(lon, lat, size=n, color=n), alpha=.5,data=map_counts)+
scale_color_gradient(low='blue', high='red')+
guides(size=FALSE)+
labs(color='# Banned Books', title='Location of Banned Books')+
theme_void()
The Nazis Hated Soviet Communism
We see that Berlin of course published many of the banned books (over 1000), but also many of the books came from Moscow. These are, again, likely related to Communism and the Russian Revolution, which occurred just a decade or so earlier.
We also can see relatively more books coming from major cities such as London, Paris, and Vienna. Interesting, Switzerland seems to have published many books as well.
Topics and Locations of Banned Books
Here we will look at the top words banned from each location to hopefully get a feel for the kinds of ideas in books published in the various cities.
top_words <- df%>%
unnest_tokens(word, title)%>%
anti_join(custom_stops)%>%
count(firsteditionpublicationplace,word)%>%
arrange(desc(n))%>%
group_by(firsteditionpublicationplace)%>%
top_n(1,n)%>%
filter(n>1)%>%
inner_join(map_counts, by='firsteditionpublicationplace')library(ggrepel)
#get new map to see colors better
water_map <- get_map('Europe', zoom=4, maptype = 'watercolor')
ggmap(water_map)+
geom_text_repel(aes(label= word,lon, lat, size=log(n.y)),min.segment.length=.9,segment.alpha = .2,color='black', force=2,data=top_words)+
guides(size=FALSE)+
scale_size(range = c(1, 5))+
theme_void()+
labs(title='Top Words by City')
Love and Revolution Coming Out of Berlin
This graphic gives us a feel for which ideas the Nazis wanted to control and where the ideas were originating from. The size of the word is proportional to the number of titles containing the word.
Love and Revolution were coming mainly from Berlin, which was known at the time for having a burgeoning Communist party that the Nazis obviously were not a fan of. It appears the Nazis were also fighting off counter-propaganda from the Soviet Union.
In the south of Germany you can see references to the Catholic church, and in Vienna you can see suppression of ‘Sittengeschichten,’ which translates to ‘history of morality.’
Again, these examples show the extent to which the Nazis waged a culture war on media in order to control and limit the free expression of ideas that went against the party’s social, historical, and religious narrative.
This is exactly why Trump’s war on the media sets such a dangerous precedent: by controlling how the populace understands its reality, those in power gain the ability to emotionally manipulate and agitate them in predictable ways.
Which Authors Had the Most Banned Books?
To get a better idea of which authors the Nazis found most repugnant, we will count the authors with the most banned books and then give a (randomly selected) example title to understand the type of books written by that author.
df_authors <- df%>%
filter(name != 'unknown')%>%
count(name, sort=T)%>%
filter(n > 4)top_title <- df%>%
filter(name != 'unknown')%>%
count(name,title, sort=T)%>%
filter(name %in% df_authors$name)%>%
group_by(name)%>%
slice(1)tot_count <- df%>%
filter(name != 'unknown')%>%
count(name, sort=T)%>%
filter(name %in% df_authors$name)%>%
group_by(name)%>%
slice(1)%>%
inner_join(top_title, by='name')#PLOTs
ggplot(tot_count, aes(reorder(name,n.x),n.x, fill=n.x))+
geom_col()+
geom_label(aes(x=reorder(name,n.x), y= 2, label=title),color='white', size=2.5)+
coord_flip()+
theme(axis.text.y = element_text(size=7))+
labs(y='# Books Banned', title='Authors with Most Banned Books', subtitle='(example title)', fill='# Banned Books')+
theme_minimal()
The Nazis Believed The Free Expression of New Ideas Is Dangerous
It is interesting for me to see that Rudolf Steiner is one of the most banned authors. There are now many ‘Rudolf Steiner Schools’ all over Germany and the US. Also Ludendorff was one of the most famous German military leaders in WWI, and later was part of the Putsch that attempted to assassinate Hitler unsuccessfully in Munich. It’s not surprising his books were banned.
The relatively benign titles listed here show just how worried the Nazis were about any books related to history, mythology, morality and sexuality (Caeseren, Aphrodite, The Sex life of Women, The Big Sin).
One particularly strange title is “Die Hochfrequenz als Verjuegungsmittel”, or, roughly translated ‘Using High Frequency Waves in Order to Look Younger.” I’m guessing this book went against the Nazi party stance on scientific research.
Which Authors and Topics Were Most Banned?
To conclude, we’ll use a treemap to see the most frequent words used in titles from the most frequently banned authors. We should be able to get a rough view of the type of titles each author wrote.
df%>%
filter(name != 'unknown')%>%
unnest_tokens(word, title)%>%
anti_join(custom_stops)%>%
count(name, word, sort=T)%>%
group_by(name)%>%
slice(which.max(n))%>%
arrange(desc(n))%>%
head(200)%>%
treemap(index = c('name', 'word'),
align.labels = list(c("left", "top"), c("center", "bottom")),
vSize='n',
type='index',
vColor='white',
fontsize.labels = c(6,6),
fontcolor.labels=c("black","white"),
title='Frequent Words by Author')
Erasing Jewish History
The size of the rectangle is proportional to the number of banned books from the author. We can see Theodor Hendrik Van der Velde (a Dutch Gynecologist and partial discoverer of the curve of human body temperature) wrote books about marriage ( Ehe), while Siegfried Lichtenstaedten wrote often about topics related to Judaism. He published works dealt with topics related to political questions of Jewish history, law, and customs. Sadly, he was murdered in a Ghetto in Theresienstadt in 1942, according to Wikipedia. I encourage you to Google some of these people to learn more about their writings and ideas.
Beware of any politician or political party which limits the free expression of ideas in society, particularly those relating to the history and culture of particular groups.
This list of books highlights the fact that topics which are seemingly unrelated to politics, such as morality tales and mythology, can be appropriated and used by those in power to control popular discourse and keep opposing ideas away from young people, who might be willing to revolt against the system. If the party narrative is pushed hard enough and long enough, people will start to believe it. Perhaps this was inspiration behind Orwell’s 1984.
Regardless of your view of certain media publishers, such as the New York Times or CNN, the next time a political figure says they are the ‘enemy of the people,’ you should remind yourself that the Nazis used the very same tactic to carry out one of the most heinous crimes against humanity and plunge the world into one of the most destructive wars ever fought.
Originally published at https://greenet09.github.io on August 14, 2018.
