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Compute the delta distances (from its two variants) of all pairs of documents in a tidy table.
pairwise_delta(tbl, item, feature, value, method = "burrows", ...)pairwise_delta_(tbl, item, feature, value, method = "burrows", ...)
Table
Item to compare; will end up in item1
and
item2
columns
Column describing the feature that links one item to others
Value
Distance measure to be used; see dist()
Extra arguments passed on to squarely()
,
such as diag
and upper
squarely()
library(janeaustenr)
library(dplyr)
library(tidytext)
# closest documents in terms of 1000 most frequent words
closest <- austen_books() %>%
unnest_tokens(word, text) %>%
count(book, word) %>%
top_n(1000, n) %>%
pairwise_delta(book, word, n, method = "burrows") %>%
arrange(delta)
closest
closest %>%
filter(item1 == "Pride & Prejudice")
# to remove duplicates, use upper = FALSE
closest <- austen_books() %>%
unnest_tokens(word, text) %>%
count(book, word) %>%
top_n(1000, n) %>%
pairwise_delta(book, word, n, method = "burrows", upper = FALSE) %>%
arrange(delta)
# Can also use Argamon's Linear Delta
closest <- austen_books() %>%
unnest_tokens(word, text) %>%
count(book, word) %>%
top_n(1000, n) %>%
pairwise_delta(book, word, n, method = "argamon", upper = FALSE) %>%
arrange(delta)
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