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A Word Never Comes Alone. A Glance at Cooccurences

Enumerating words can be helpful. With a simple command (tokens_ngrams), in R we also got lists of word pairs and triples and so on. But usually we want to know which words appear within the same documents. What about co-occurences within the same song? Which words appear in the same songs? With the fcm() command in R we obtain a neat little table, more or less like the following. 

                ich     du     gut     liebe     kalt     bitte     sonne

ich           2775 1289  474    550      352      25       143

du            0       920  209   183       279      25       19

gut           0       0      91       19         0         2         20

lust          627    1     2         0           280     0          1

deutschl  209    532  0         76        152      0         171

liebe                                    140       55       41         11

kalt                                                     84       28         4

bitte                                                             36         0

sonne                                                                       166


As a plot: 





We see a bridge from "ich" to "du", to "lust", "liebe" and a lighter one to "kalt". This really looks like the word center of Rammstein songs. 

From the table, we see that "liebe" has no connection to "ich" and "du", while "lust" co-occurs with "ich" and "kalt". Reflect!

Note: Some of the above numbers are very high because co-occurences are calculated within a V*V matrix. Hence, the square of the term frequency is the basis. For definitive results, we should calculate the relative frequency. 

technically
Packages quanteda, readtext

my_stopwords <- stopwords("de")%>%
  char_remove(pattern=c("ich", "du"))
toks_fund <- tokens(basis, remove_punct = TRUE, remove_numbers = TRUE, remove_symbol = TRUE)%>%
        tokens_remove(pattern = my_stopwords)
matrixa <- dfm(toks_fund)

toks_zusammen <- fcm(matrixa)
feat <- names(topfeatures(toks_zusammen, 20))
fcmat_tokszus_subset <- toks_zusammen %>%
  fcm_select(feat)
tplot_zusammen <- textplot_network(fcmat_tokszus_subset)
set.seed(134)
tplot_zusammen
write.table(fcmat_tokszus_subset, file = "")


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