quanteda 3.0 is a major release that improves functionality, completes the modularisation of the package begun in v2.0, further improves function consistency by removing previously deprecated functions, and enhances workflow stability and consistency by deprecating some shortcut steps built into some functions.
Modularisation: We have now separated the textplot_*() functions from the main package into a separate package quanteda.textplots, and the textstat_*() functions from the main package into a separate package quanteda.textstats. This completes the modularisation begun in v2 with the move of the textmodel_*() functions to the separate package quanteda.textmodels. quanteda now consists of core functions for textual data processing and management.
The package dependency structure is now greatly reduced, by eliminating some unnecessary package dependencies, through modularisation, and by addressing complex downstream dependencies in packages such as stopwords. v3 should serve as a more lightweight and more consistent platform for other text analysis packages to build on.
We have added non-standard evaluation for by and groups arguments to access object docvars:
*_sample() functions’ argument by, and groups in the *_group() functions, now take unquoted document variable (docvar) names directly, similar to the way the subset argument works in the *_subset() functions.by = "document" formerly sampled from docid(x), but this functionality is now removed. Instead, use by = docid(x) to replicate this functionality.groups, the default is now docid(x), which is now documented more completely. See ?groups and ?docid.dfm() has a new argument, remove_padding, for removing the “pads” left behind after removing tokens with padding = TRUE. (For other extensive changes to dfm(), see “Deprecated” below.)
tokens_group(), formerly internal-only, is now exported.
corpus_sample(), dfm_sample(), and tokens_sample() now work consistently (#2023).
The kwic() return object structure has been redefined, and built with an option to use a new function index() that returns token spans following a pattern search. (#2045 and #2065)
The punctuation regular expression and that for matching social media usernames has now been redefined so that the valid Twitter username @_ is now counted as a “tag” rather than as “punctuation”. (#2049)
The data object data_corpus_inaugural has been updated to include the Biden 2021 inaugural address.
A new system of validators for input types now provides better argument type and value checking, with more consistent error messages for invalid types or values.
Upon startup, we now message the console with the Unicode and ICU version information. Because we removed our redefinition of View() (see below), the former conflict warning is now gone.
as.character.corpus() now has a use.names = TRUE argument, similar to as.character.tokens() (but with a different default value).
The main potentially breaking changes in version 3 relate to the deprecation or elimination of shortcut steps that allowed functions that required tokens inputs to skip the tokens creation step. We did this to require users to take more direct control of tokenization options, or to substitute the alternative tokeniser of their choice (and then coercing it to tokens via [as.tokens()]). This also allows our function behaviour to be more consistent, with each function performing a single task, rather than combining functions (such as tokenisation and constructing a matrix).
The most common example involves constructing a dfm directly from a character or corpus object. Formerly, this would construct a tokens object internally before creating the dfm, and allowed passing arguments to tokens() via .... This is now deprecated, although still functional with a warning.
We strongly encourage either creating a tokens object first, or piping the tokens return to dfm() using %>%. (See examples below.)
We have also deprecated direct character or corpus inputs to [kwic()], since this also requires a tokenised input.
The full listing of deprecations is:
dfm.character() and dfm.corpus() are deprecated. Users should create a tokens object first, and input that to dfm().
dfm(): As of version 3, only tokens objects are supported as inputs to dfm(). Calling dfm() for character or corpus objects is still functional, but issues a warning. Convenience passing of arguments to tokens() via ... for dfm() is also deprecated, but undocumented, and functions only with a warning. Users should now create a tokens object (using tokens() from character or corpus inputs before calling dfm().
kwic(): As of version 3, only tokens objects are supported as inputs to kwic(). Calling kwic() for character or corpus objects is still functional, but issues a warning. Passing arguments to tokens() via ... in kwic() is now disabled. Users should now create a tokens object (using tokens() from character or corpus inputs before calling kwic().
Shortcut arguments to dfm() are now deprecated. These are still active, with a warning, although they are no longer documented. These are:
stem – use tokens_wordstem() or dfm_wordstem() instead.select, remove – use tokens_select() / dfm_select() or tokens_remove() / dfm_remove() instead.dictionary, thesaurus – use tokens_lookup() or dfm_lookup() instead.valuetype, case_insensitive – these are disabled; for the deprecated arguments that take these qualifiers, they are fixed to the defaults "glob" and TRUE.groups – use tokens_group() or dfm_group() instead.texts() and texts<- are deprecated.
as.character.corpus() to turn a corpus into a simple named character vector.corpus_group() instead of texts(x, groups = ...) to aggregate texts by a grouping variable.[<- instead of texts()<- for replacing texts in a corpus object.See note above under “Changes” about the textplot_*() and textstat_*() functions.
The following functions have been removed:
corpuszip objects.View() functionsas.wfm() and as.DocumentTermMatrix() (the same functionality is available via convert())metadoc() and metacorpus()
corpus_trimsentences() (replaced by corpus_trim())tortl functionsdfm objects can no longer be used as a pattern in dfm_select() (formerly deprecated).
margin argument. Instead, dfm_sample() now samples only on documents, the same as corpus_sample() and tokens_sample(); andby = "document" – use by = docid(x) instead.dictionary_edit(), char_edit(), and list_edit() are removed.
dfm_weight() - formerly deprecated "scheme" options are now removed.
tokens() - formerly deprecated options remove_hyphens and remove_twitter are now removed. (Use split_hyphens instead, and the default tokenizer always now preserves Twitter and other social media tags.)
Special versions of head() and tail() for corpus, dfm, and fcm objects are now removed, since the base methods work fine for these objects. The main consequence was the removal of the nf option from the methods for dfm and fcm objects, which limited the number of features. This can be accomplished using the index operator [ instead, or for printing, by specifying print(x, max_nfeat = 6L) (for instance).
Fixed a bug causing topfeatures(x, group = something) to fail with weighted dfms (#2032).
kwic() is more stable and does not crash when a vector is supplied as the window argument (#2008).
Allow use of multi-threading with more than two threads by fixing quanteda_options().
Mentions of the now-removed ngrams option in dfm(x, ...) has now been removed from the dfm documentation. (#1990)
Handling for some early-cycle v2 dfm object is improved, to ensure that they are updated to the latest object format. (#2097)