require(quanteda)
require(quanteda.corpora)
This corpus contains 6,000 Guardian news articles from 2012 to 2016.
news_corp <- download('data_corpus_guardian')
By collocation analysis, we can identify contiguous collocations of words. One of the most common types of multi-word expressions is proper names, which can be identified simply based on capitalization in English texts.
news_toks <- tokens(news_corp, remove_punct = TRUE)
cap_col <- tokens_select(news_toks, '^[A-Z]', valuetype = 'regex', case_insensitive = FALSE, padding = TRUE) %>%
textstat_collocations(min_count = 100)
head(cap_col, 20)
## collocation count count_nested length lambda z
## 1 david cameron 861 0 2 8.159403 147.28033
## 2 donald trump 774 0 2 8.327021 122.69669
## 3 george osborne 364 0 2 8.660850 107.62167
## 4 hillary clinton 527 0 2 9.106769 102.39786
## 5 new york 1016 0 2 10.447920 100.26710
## 6 islamic state 330 0 2 9.802253 98.14614
## 7 white house 479 0 2 9.922038 96.17659
## 8 european union 351 0 2 8.261629 94.76270
## 9 jeremy corbyn 244 0 2 8.729599 90.79494
## 10 boris johnson 245 0 2 9.664231 84.76850
## 11 bernie sanders 394 0 2 9.901472 84.61828
## 12 guardian australia 237 0 2 6.327399 83.68384
## 13 northern ireland 205 0 2 9.883258 83.25817
## 14 home office 216 0 2 9.681955 78.79433
## 15 ed miliband 174 0 2 9.868133 78.44900
## 16 ted cruz 417 0 2 10.756439 77.87897
## 17 barack obama 344 0 2 9.775375 77.72771
## 18 south africa 172 0 2 7.568724 77.61283
## 19 south carolina 271 0 2 9.404827 76.80194
## 20 black friday 190 0 2 8.459064 76.80003
You can also discover collocations larger than two words.
cap_col2 <- tokens_select(news_toks, '^[A-Z]', valuetype = 'regex', case_insensitive = FALSE, padding = TRUE) %>%
textstat_collocations(min_count = 100, size = 3)
head(cap_col2, 20)
## collocation count count_nested length lambda
## 1 international monetary fund 101 0 3 2.2425567
## 2 new york times 128 0 3 -0.5072592
## z
## 1 1.0791473
## 2 -0.3338525
If you find textstat_collocations() is talking too much time, increase the min_count threashold to speed up the estimation. You also do not need to set sizes larger than 2 to compound multi-word expressions, because overlapped collocations are chained if join = TRUE in tokens_compound().