quanteda 2.1.0 2020-07-05

Changes

  • Added block_size to quanteda_options() to control the number of documents in blocked tokenization.
  • Fixed print.dictionary2() to control the printing of nested levels with max_nkey (#1967)
  • Added textstat_summary() to provide detailed information about dfm, tokens and corpus objects. It will replace summary() in future versions.
  • Fixed a performance issue causing slowdowns in tokenizing (using the default what = "word") corpora with large numbers of documents that contain social media tags and URLs that needed to be preserved (such a large corpus of Tweets).
  • Updated the (default) “word” tokenizer to preserve hashtags and usernames better with non-ASCII text, and made these patterns user-configurable in quanteda_options(). The following are now preserved: “#政治” as well as Weibo-style hashtags such as “#英国首相#”.
  • convert(x, to = "data.frame") now outputs the first column as “doc_id” rather than “document” since “document” is a commonly occurring term in many texts. (#1918)
  • Added new methods char_select(), char_keep(), and char_remove() for easy manipulation of character vectors.
  • Added dictionary_edit() for easy, interactive editing of dictionaries, plus the functions char_edit() and list_edit() for editing character and list of character objects.
  • Added a method to textplot_wordcloud() that plots objects from textstat_keyness(), to visualize keywords either by comparison or for the target category only.
  • Improved the performance of kwic() (#1840).
  • Added new logsmooth scheme to dfm_weight().
  • Added new textstat_summary() method, which returns summary information about the tokens/types/features etc in an object. It also caches summary information so that this can be retrieved on subsequent calls, rather than re-computed.

Bug fixes and stability enhancements

quanteda 2.1.1 2020-07-27

Changes

Bug fixes and stability enhancements