quanteda 1.0.0 2018-01-28

New Features

  • Added vertex_labelfont to textplot_network().
  • Added textmodel_lsa() for Latent Semantic Analysis models.
  • Added textmodel_affinity() for the Perry and Benoit (2017) class affinity scaling model.
  • Added Chinese stopwords.
  • Added a pkgdown vignette for applications in the Chinese language.
  • Added textplot_network() function.
  • The stopwords() function and the associated internal data object data_char_stopwords have been removed from quanteda, and replaced by equivalent functionality in the stopwords package.
  • Added tokens_subset(), now consistent with other *_subset() functions (#1149).

Bug fixes and stability enhancements

  • Performance has been improved for fcm() and for textmodel_wordfish().
  • dfm() now correctly passes through all ... arguments to tokens(). (#1121)
  • All dfm_*() functions now work correctly with empty dfm objects. (#1133)
  • Fixed a bug in dfm_weight() for named weight vectors (#1150)
  • Fixed a bug preventing textplot_influence() from working (#1116).

Behaviour Changes

  • The convenience wrappers to convert() are simplified and no longer exported. To convert a dfm, convert() is now the only official function.
  • nfeat() replaces nfeature(), which is now deprecated. (#1134)
  • textmodel_wordshoal() has been removed, and relocated to a new package (wordshoal).
  • The generic wrapper function textmodel(), which used to be a gateway to specific textmodel_*() functions, has been removed.
  • (Most of) the textmodel_*() have been reimplemented to make their behaviour consistent with the lm/glm() families of models, including especially how the predict, summary, and coef methods work (#1007, #108).
  • The GitHub home for the repository has been moved to https://github.com/quanteda/quanteda.