Rammstein Read by the Machine

2879 words (tokens) are not very much, unique tokens: 1570, when stemmed: 1317. All the same, finding patterns across the 97 poems in Till Lindemann's "Quiet Nights" seems to be difficult. Looking for n-gams and skipgrams: found nothing that went beyond the limits of single poems. Asking with R Quanteda for co-occurences, with n=50 we get a cloud: What we see? A predominance of words for human and animal bodies or parts of them: "hund", "mund", "haar", "schweiß", "blut", "fleisch", "herz" .... Inquiring on these elements could be an interesting project. As a net of words, though, the entire image is only confusing. Lowering n to 20, the picture gets clearer, but the connecting lines are really weak. "Dass" should be eliminated, right.  Going down to n=7. The animals have vanished, "heart" and "face" are the only remaning parts of the body. At the end, after stemming and low...

Till Lindemann, lead singer of the Rammstein group, has also published some collections of poems. You should not forget: he is the son of Werner Lindemann, who used to be a prominent writer in the times of the socialist German Democratic Rebublic.  As I am (together with Claudia Lisa Moeller) translating one of these books,  "In stillen Nächten"/ "On Quiet Nights" (English translation by Ehren Fordyce,  Raw Dog Screaming Press, Bowie MD in 2025)  into Italian, I took out my R Quanteda package in order to take a more distant view on the poems.  The most frequent words ("stopwords" excluded) in Lindemann's poems are "Herz" ("heart"), which appears 33 times, and "Liebe" ("love") with 26 occurrences. This might seem similar to the frequencies in Rammstein songs, where we read the leading word "Liebe" 46 times, followed  by "Mann"/ man (45).  We might assume that, since "Herz" is often ta...

What do we mean when asking what these song texts are about?  It may mean we are looking for topics, considering each single song as a net of themes. Maybe one  text is about the milkman and a boy and about love. We would consider certain words in the text as representation of these topics (maybe two of them). Bottle, white, milk, door could be seen as related to the milkman, kiss and forever and flowers to love and to the boy, too.  For us humans, the work of relating words to topics or topics to texts is usually conceptual.  We do not need to have a look into the real world, not even into texts, in order to see a relation between the color white and the front door once the milkman is named.  The machine instead needs data, empirical evidence. Working its way through the texts, it could make a list of words and the single texts where they occur, maybe calculating the frequency of the word within the text and within the entire corpus of songs. But this is not a ...