Introduces the tokens_xptr objects that extend the tokens objects with external pointers for a greater efficiency. Once tokens objects are converted to tokens_xptr objects using as.tokens_xptr(), tokens_*.tokens_xptr() methods are called automatically.
Improved C++ functions to allow the users to change the number of threads for parallel computing in more flexible manner using quanteda_options(). The value of threads can be changed in the middle of analysis pipeline.
Makes "word4" the default (word) tokeniser, with improved efficiency, language handling, and customisation options.
Replaced all occurrences of the magrittr %>% pipe with the R pipe |> introduced in R 4.1, although the %>% pipe is still re-exported and therefore available to all users of quanteda without loading any additional packages.
Added min_ntoken and max_ntoken to tokens_subset() and dfm_subset() to extract documents based on number of tokens easily. It is equivalent to selecting documents using ntoken().
Added a new argument apply_if that allows a tokens-based operation to apply only to documents that meet a logical condition. This argument has been added to tokens_select(), tokens_compound(), tokens_replace(), tokens_split(), and tokens_lookup(). This is similar to applying purrr::map_if() to a tokens object, but is implemented within the function so that it can be performed efficiently in C++.
Added new arguments append_key, separator and concatenator to tokens_lookup(). These allow tokens matched by dictionary values to be retained with their keys appended to them, separated by separator. The addition of the concatenator argument allows additional control at the lookup stage for tokens that will be concatenated from having matched multi-word dictionary values. (#2324)
Added a new argument remove_padding to ntoken() and ntype() that allows for not counting padding that might have been left over from tokens_remove(x, padding = TRUE). This changes the previous number of types from ntype() when pads exist, by counting pads by default. (#2336)
Removed dependency on RcppParallel to improve the stability of the C++ code. This change requires the users of Linux-like OS to install the Intel TBB library manually to enable parallel computing.
bootstrap_dfm() was removed for character and corpus objects. The correct way to bootstrap sentences is not to tokenize them as sentences and then bootstrap them from the dfm. This is consistent with requiring the user to tokenise objects prior to forming dfms or other “downstream” objects.
dfm() no longer works on character or corpus objects, only on tokens or other dfm objects. This was deprecated in v3 and removed in v4.
Very old arguments to dfm() options that were not visible but worked with warnings (such as stem = TRUE) are removed.
Deprecated or renamed arguments formerly passed in tokens() that formerly mapped to the v3 arguments with a warning are removed.
Methods for readtext objects are removed, since these are data.frame objects that are straightforward to convert into a corpus object.
topfeatures() no longer works on an fcm object. (#2141)
nsentence() – use lengths(tokens(x, what = "sentence")) instead;ntype() – use ntype(tokens(x)) instead; and.ntoken() – use ntoken(tokens(x)) instead.char_ngrams() – use tokens_ngrams(tokens(x)) instead.corpus.kwic() is deprecated, with the suggestion to form a corpus from using tokens_select(x, window = ...) instead.tokens_group() works efficiently even when the number of documents and groups are very large.