Quantitative Analysis of Textual Data

[Up] [Top]

Documentation for package ‘quanteda’ version 0.9.9-24

Help Pages

A C D F H I K M N Q S T

quanteda-package An R package for the quantitative analysis of textual data

-- A --

as.character.corpus get or assign corpus texts
as.character.tokens coercion and checking functions for tokens objects
as.corpus.corpuszip coerce a compressed corpus to a standard corpus
as.data.frame.dfm coerce a dfm to a matrix or data.frame
as.dfm coercion and checking functions for dfm objects
as.kwic locate keywords-in-context
as.list.dist coerce a dist object into a list
as.list.tokens coercion and checking functions for tokens objects
as.matrix.dfm coerce a dfm to a matrix or data.frame
as.tokens coercion and checking functions for tokens objects
as.tokens.list coercion and checking functions for tokens objects

-- C --

char_ngrams create ngrams and skipgrams from tokens
char_segment segment texts into component elements
char_tolower convert the case of character objects
char_toupper convert the case of character objects
char_wordstem stem the terms in an object
collocations detect collocations from text
convert convert a dfm to a non-quanteda format
corpus construct a corpus object
corpus_reshape change the document units of a corpus
corpus_sample randomly sample documents from a corpus
corpus_segment segment texts into component elements
corpus_subset extract a subset of a corpus

-- D --

data_char_inaugural US presidential inaugural address texts
data_char_mobydick text of Herman Melville's Moby Dick
data_char_sampletext a paragraph of text for testing various text-based functions
data_char_ukimmig2010 immigration-related sections of 2010 UK party manifestos
data_corpus_inaugural US presidential inaugural address texts
data_corpus_irishbudget2010 Irish budget speeches from 2010
data_dfm_LBGexample dfm from data in Table 1 of Laver, Benoit, and Garry (2003)
dfm create a document-feature matrix
dfm_compress compress a dfm or fcm by combining identical dimension elements
dfm_lookup apply a dictionary to a dfm
dfm_remove select features from a dfm or fcm
dfm_sample randomly sample documents or features from a dfm
dfm_select select features from a dfm or fcm
dfm_smooth weight the feature frequencies in a dfm
dfm_sort sort a dfm by frequency of one or more margins
dfm_tolower convert the case of the features of a dfm and combine
dfm_toupper convert the case of the features of a dfm and combine
dfm_trim trim a dfm using frequency threshold-based feature selection
dfm_weight weight the feature frequencies in a dfm
dfm_wordstem stem the terms in an object
dictionary create a dictionary
docnames get or set document names
docnames<- get or set document names
docvars get or set for document-level variables
docvars<- get or set for document-level variables

-- F --

fcm create a feature co-occurrence matrix
fcm_compress compress a dfm or fcm by combining identical dimension elements
fcm_remove select features from a dfm or fcm
fcm_select select features from a dfm or fcm
fcm_sort sort an fcm in alphabetical order of the features
fcm_tolower convert the case of the features of a dfm and combine
fcm_toupper convert the case of the features of a dfm and combine
featnames get the feature labels from a dfm

-- H --

head.dfm return the first or last part of a dfm

-- I --

is.collocations check if an object is collocations type
is.dfm coercion and checking functions for dfm objects
is.dictionary check if an object is a dictionary
is.fcm create a feature co-occurrence matrix
is.kwic locate keywords-in-context
is.tokens coercion and checking functions for tokens objects

-- K --

kwic locate keywords-in-context

-- M --

metacorpus get or set corpus metadata
metacorpus<- get or set corpus metadata
metadoc get or set document-level meta-data
metadoc<- get or set document-level meta-data

-- N --

ndoc count the number of documents or features
nfeature count the number of documents or features
nscrabble count the Scrabble letter values of text
nsentence count the number of sentences
nsyllable count syllables in a text
ntoken count the number of tokens or types
ntype count the number of tokens or types

-- Q --

quanteda An R package for the quantitative analysis of textual data

-- S --

sequences find variable-length collocations with filtering
sparsity compute the sparsity of a document-feature matrix
stopwords access built-in stopwords

-- T --

tail.dfm return the first or last part of a dfm
textmodel fit a text model
textmodel-method fit a text model
textmodel_ca correspondence analysis of a document-feature matrix
textmodel_NB Naive Bayes classifier for texts
textmodel_wordfish wordfish text model
textmodel_wordscores Wordscores text model
textmodel_wordshoal wordshoal text model
textplot_scale1d plot a fitted wordfish model
textplot_wordcloud plot features as a wordcloud
textplot_xray plot the dispersion of key word(s)
texts get or assign corpus texts
texts<- get or assign corpus texts
textstat_dist Distance matrix between documents and/or features
textstat_keyness calculate keyness statistics
textstat_lexdiv calculate lexical diversity
textstat_readability calculate readability
textstat_simil Distance matrix between documents and/or features
tokens tokenize a set of texts
tokens_compound convert token sequences into compound tokens
tokens_lookup apply a dictionary to a tokens object
tokens_ngrams create ngrams and skipgrams from tokens
tokens_remove select or remove tokens from a tokens object
tokens_select select or remove tokens from a tokens object
tokens_skipgrams create ngrams and skipgrams from tokens
tokens_tolower convert the case of tokens
tokens_toupper convert the case of tokens
tokens_wordstem stem the terms in an object
topfeatures list the most frequent features