tidytext 0.2.5

• reorder_within() now handles multiple variables, thanks to @tmastny (#170)
• Move stopwords to Suggests so tidytext can be installed on older versions of R
• Pass to_lower argument to other tokenizing functions, for more consistent behavior (#175)
• Add glance() method for stm’s estimated regressions, thanks to @vincentarelbundock (#176)

tidytext 0.2.4

• Update tidying test for new tibble release (inner names for columns)
• Deprecate SE versions of main functions (have long been replaced by tidy eval semantics)
• Improve error handling throughout

tidytext 0.2.3

• Wrapper tokenization functions for n-grams, characters, sentences, tweets, and more, thanks to @ColinFay (#137).
• Simplify get_sentiments() thanks to @jennybc (#151).
• Fix flaky tests for corpus tidiers.

tidytext 0.2.2

• Access NRC lexicon via textdata package

tidytext 0.2.1

• Fix bug in augment() function for stm topic model.
• Warn when tf-idf is negative, thanks to @EmilHvitfeldt (#112).
• Switch from importing broom to importing generics, for lighter dependencies (#133).
• Add functions for reordering factors (such as for ggplot2 bar plots) thanks to @tmastny (#110).
• Update to tibble() where appropriate, thanks to @luisdza (#136).
• Clarify documentation about impact of lowercase conversion on URLs (#139).
• Change how sentiment lexicons are accessed from package (remove NRC lexicon entirely, access AFINN and Loughran lexicons via textdata package so they are no longer included in this package).

tidytext 0.2.0

• Improvements to documentation (#117)
• Fix for NSE thanks to @lepennec (#122).
• Tidier for estimated regressions from stm package thanks to @jefferickson (#115).
• Tidier for correlated topic model from topicmodels package (#123).

tidytext 0.1.9

• Updates to documentation (#109) thanks to Emil Hvitfeldt.
• Add new tokenizers for tweets, Penn Treebank to unnest_tokens().
• Better error message (#111) and code styling.
• Declare dependency for tests.

tidytext 0.1.8

• Updates to documentation (#102), README, and vignettes.
• Add tokenizing by character shingles thanks to Kanishka Misra (#105).
• Fix tests for skip grams thanks to Lincoln Mullen (#106).

tidytext 0.1.7

• Updated more docs/tests so package can build on R-oldrel. (Still trying!)

tidytext 0.1.6

• unnest_tokens can now unnest a data frame with a list column (which formerly threw the error unnest_tokens expects all columns of input to be atomic vectors (not lists)). The unnested result repeats the objects within each list. (It’s still not possible when collapse = TRUE, in which tokens can span multiple lines).
• Add get_tidy_stopwords() to obtain stopword lexicons in multiple languages in a tidy format.
• Add a dataset nma_words of negators, modals, and adverbs that affect sentiment analysis (#55).
• Updated various vignettes/docs/tests so package can build on R-oldrel.

tidytext 0.1.5

• Change how NA values are handled in unnest_tokens so they no longer cause other columns to become NA (#82).
• Update tidiers and casters to align with quanteda v1.0 (#87).
• Handle input/output object classes (such as data.table) consistently (#88).

tidytext 0.1.4

• Fix tidier for quanteda dictionary for correct class (#71).
• Add a pkgdown site.
• Convert NSE from underscored function to tidyeval (unnest_tokens, bind_tf_idf, all sparse casters) (#67, #74).
• Added tidiers for topic models from the stm package (#51).

tidytext 0.1.3

• get_sentiments now works regardless of whether tidytext has been loaded or not (#50).
• unnest_tokens now supports data.table objects (#37).
• Fixed to_lower parameter in unnest_tokens to work properly for all tokenizing options.
• Updated tidy.corpus, glance.corpus, tests, and vignette for changes to quanteda API
• Removed the deprecated pair_count function, which is now in the in-development widyr package
• Added tidiers for LDA models from the mallet package
• Added the Loughran and McDonald dictionary of sentiment words specific to financial reports
• unnest_tokens preserves custom attributes of data frames and data.tables

tidytext 0.1.2

• Updated DESCRIPTION to require purrr >= 0.1.1.
• Fixed cast_sparse, cast_dtm, and other sparse casters to ignore groups in the input (#19)
• Changed unnest_tokens so that it no longer uses tidyr’s unnest, but rather a custom version that removes some overhead. In some experiments, this sped up unnest_tokens on large inputs by about 40%. This also moves tidyr from Imports to Suggests for now.
• unnest_tokens now checks that there are no list columns in the input, and raises an error if present (since those cannot be unnested).
• Added a format argument to unnest_tokens so that it can process html, xml, latex or man pages using the hunspell package, though only when token = "words".
• Added a get_sentiments function that takes the name of a lexicon (“nrc”, “bing”, or “sentiment”) and returns just that sentiment data frame (#25)

tidytext 0.1.1

• Added documentation for n-grams, skip n-grams, and regex
• Added codecov and appveyor
• Added tidiers for LDA objects from topicmodels and a vignette on topic modeling
• Added function to calculate tf-idf of a tidy text dataset and a tf-idf vignette
• Fixed a bug when tidying by line/sentence/paragraph/regex and there are multiple non-text columns
• Fixed a bug when unnesting using n-grams and skip n-grams (entire text was not being collapsed)
• Added ability to pass a (custom tokenizing) function to token. Also added a collapse argument that makes the choice whether to combine lines before tokenizing explicit.
• Changed tidy.dictionary to return a tbl_df rather than a data.frame
• Updated cast_sparse to work with dplyr 0.5.0
• Deprecated the pair_count function, which has been moved to pairwise_count in the widyr package. This will be removed entirely in a future version.

tidytext 0.1.0

• Initial release for text mining using tidy tools