augment.CTM |
Tidiers for LDA and CTM objects from the topicmodels package |
augment.jobjRef |
Tidiers for Latent Dirichlet Allocation models from the mallet package |
augment.LDA |
Tidiers for LDA and CTM objects from the topicmodels package |
augment.STM |
Tidiers for Structural Topic Models from the stm package |
bind_tf_idf |
Bind the term frequency and inverse document frequency of a tidy text dataset to the dataset |
cast_dfm |
Casting a data frame to a DocumentTermMatrix, TermDocumentMatrix, or dfm |
cast_dtm |
Casting a data frame to a DocumentTermMatrix, TermDocumentMatrix, or dfm |
cast_sparse |
Create a sparse matrix from row names, column names, and values in a table. |
cast_tdm |
Casting a data frame to a DocumentTermMatrix, TermDocumentMatrix, or dfm |
corpus_tidiers |
Tidiers for a corpus object from the quanteda package |
dictionary_tidiers |
Tidy dictionary objects from the quanteda package |
get_sentiments |
Get a tidy data frame of a single sentiment lexicon |
get_stopwords |
Get a tidy data frame of a single stopword lexicon |
glance.corpus |
Tidiers for a corpus object from the quanteda package |
glance.CTM |
Tidiers for LDA and CTM objects from the topicmodels package |
glance.estimateEffect |
Tidiers for Structural Topic Models from the stm package |
glance.LDA |
Tidiers for LDA and CTM objects from the topicmodels package |
glance.STM |
Tidiers for Structural Topic Models from the stm package |
lda_tidiers |
Tidiers for LDA and CTM objects from the topicmodels package |
mallet_tidiers |
Tidiers for Latent Dirichlet Allocation models from the mallet package |
nma_words |
English negators, modals, and adverbs |
parts_of_speech |
Parts of speech for English words from the Moby Project |
reorder_func |
Reorder an x or y axis within facets |
reorder_within |
Reorder an x or y axis within facets |
scale_x_reordered |
Reorder an x or y axis within facets |
scale_y_reordered |
Reorder an x or y axis within facets |
sentiments |
Sentiment lexicon from Bing Liu and collaborators |
stm_tidiers |
Tidiers for Structural Topic Models from the stm package |
stop_words |
Various lexicons for English stop words |
tdm_tidiers |
Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package |
tidy.Corpus |
Tidy a Corpus object from the tm package |
tidy.corpus |
Tidiers for a corpus object from the quanteda package |
tidy.CTM |
Tidiers for LDA and CTM objects from the topicmodels package |
tidy.dfm |
Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package |
tidy.dfmSparse |
Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package |
tidy.dictionary2 |
Tidy dictionary objects from the quanteda package |
tidy.DocumentTermMatrix |
Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package |
tidy.estimateEffect |
Tidiers for Structural Topic Models from the stm package |
tidy.jobjRef |
Tidiers for Latent Dirichlet Allocation models from the mallet package |
tidy.LDA |
Tidiers for LDA and CTM objects from the topicmodels package |
tidy.simple_triplet_matrix |
Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package |
tidy.STM |
Tidiers for Structural Topic Models from the stm package |
tidy.TermDocumentMatrix |
Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package |
tidy_triplet |
Utility function to tidy a simple triplet matrix |
unnest_characters |
Wrapper around unnest_tokens for characters and character shingles |
unnest_character_shingles |
Wrapper around unnest_tokens for characters and character shingles |
unnest_lines |
Wrapper around unnest_tokens for sentences, lines, and paragraphs |
unnest_ngrams |
Wrapper around unnest_tokens for n-grams |
unnest_paragraphs |
Wrapper around unnest_tokens for sentences, lines, and paragraphs |
unnest_ptb |
Wrapper around unnest_tokens for Penn Treebank Tokenizer |
unnest_regex |
Wrapper around unnest_tokens for regular expressions |
unnest_sentences |
Wrapper around unnest_tokens for sentences, lines, and paragraphs |
unnest_skip_ngrams |
Wrapper around unnest_tokens for n-grams |
unnest_tokens |
Split a column into tokens |