quanteda package - RDocumentation

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About

An R package for managing and analyzing text, created by Kenneth Benoit. Supported by the European Research Council grant ERC-2011-StG 283794-QUANTESS.

For more details, see https://quanteda.io.

How to Install

The normal way from CRAN, using your R GUI or

install.packages("quanteda")

Or for the latest development version:

# devtools package required to install quanteda from Github 
devtools::install_github("quanteda/quanteda")

Because this compiles some C++ and Fortran source code, you will need to have installed the appropriate compilers.

If you are using a Windows platform, this means you will need also to install the Rtools software available from CRAN.

If you are using macOS, you should install the macOS tools, namely the Clang 6.x compiler and the GNU Fortran compiler (as quanteda requires gfortran to build). If you are still getting errors related to gfortran, follow the fixes here.

How to Use

See the quick start guide to learn how to use quanteda.

How to cite

Benoit, Kenneth, Kohei Watanabe, Haiyan Wang, Paul Nulty, Adam Obeng, Stefan Müller, and Akitaka Matsuo. (2018) “quanteda: An R package for the quantitative analysis of textual data”. Journal of Open Source Software. 3(30), 774. https://doi.org/10.21105/joss.00774.

For a BibTeX entry, use the output from citation(package = "quanteda").

Leaving Feedback

If you like quanteda, please consider leaving feedback or a testimonial here.

Contributing

Contributions in the form of feedback, comments, code, and bug reports are most welcome. How to contribute:

Fork the source code, modify, and issue a pull request through the project GitHub page. See our Contributor Code of Conduct and the all-important quanteda Style Guide.
Issues, bug reports, and wish lists: File a GitHub issue.
Usage questions: Submit a question on the quanteda channel on StackOverflow.
Contact the maintainer by email.

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Version

Install

install.packages('quanteda')

Monthly Downloads

24,111

Version

1.5.0

License

GPL-3

Maintainer

Kenneth Benoit

Last Published

July 4th, 2019

Functions in quanteda (1.5.0)

as.corpus.corpuszip

Coerce a compressed corpus to a standard corpus

Coercion and checking functions for dfm objects

Coerce a dist into a dist

Internal function to fit the likelihood scaling mixture model.

Coercion and checking functions for dictionary objects

as.data.frame.dfm

Convert a dfm to a data.frame

Coercion functions for fcm objects

View methods for quanteda

as.coefficients_textmodel

Coerce various objects to coefficients_textmodel This is a helper function used in summary.textmodel_*.

as.statistics_textmodel

Coerce various objects to statistics_textmodel

Check if font is available on the system

coerce a compressed corpus to a standard corpus

as.summary.textmodel

Assign the summary.textmodel class to a list

Compute the Moving-Average Type-Token Ratio (MATTR)

Segment texts on a pattern match

compute_lexdiv_stats

Compute lexical diversity from a dfm or tokens

Randomly sample documents from a corpus

data_corpus_irishbudget2010

Irish budget speeches from 2010

as.matrix.dist_selection

Coerce a dist_selection object to a matrix

Convert a dfm to a non-quanteda format

as.matrix.simil

Coerce a simil object into a matrix

Base method extensions for corpus objects

as.list.dist_selection

Coerce a dist_selection object into a list

as.matrix,textstat_simil_sparse-method

as.matrix method for textstat_simil_sparse

Convert an fcm to an igraph object

Coerce a dist object into a list

Internal functions for dfm objects

data-deprecated

Datasets with deprecated or defunct names

Extract a subset of a corpus

coef.textmodel_ca

Extract model coefficients from a fitted textmodel_ca object

Internal data sets

Remove sentences based on their token lengths or a pattern match

Coercion, checking, and combining functions for tokens objects

redefinition of network::as.network()

Construct a corpus object

Recast the document units of a corpus

Convert quanteda dictionary objects to the YAML format

Convert the case of the features of a dfm and combine

Get or set document-level variables

Trim a dfm using frequency threshold-based feature selection

data_dfm_lbgexample

dfm from data in Table 1 of Laver, Benoit, and Garry (2003)

Internal function for select_types() to escape regular expressions

data_corpus_dailnoconf1991

Confidence debate from 1991 Irish Parliament

data_corpus_inaugural

US presidential inaugural address texts

Bootstrap a dfm

Compute the Mean Segmental Type-Token Ratio (MSTTR)

Function extending base::attributes()

Virtual class "dfm" for a document-feature matrix

convert-wrappers

Convenience wrappers for dfm convert

data_dictionary_LSD2015

Lexicoder Sentiment Dictionary (2015)

Create a feature co-occurrence matrix

data_char_ukimmig2010

Immigration-related sections of 2010 UK party manifestos

data_char_sampletext

A paragraph of text for testing various text-based functions

generate_groups

Generate a grouping vector from docvars

Sort an fcm in alphabetical order of the features

flatten_dictionary

Flatten a hierarchical dictionary into a list of character vectors

Get the feature labels from a dfm

predict.textmodel_affinity

Prediction for a fitted affinity textmodel

predict.textmodel_nb

Prediction from a fitted textmodel_nb object

convert same-value pairs to NA in a textstat_proxy object

Internal function for select_types() to check if a string is a regular expression

Weight the feature frequencies in a dfm

Create a document-feature matrix

Match the feature set of a dfm to given feature names

print.statistics_textmodel

Implements print methods for textmodel_statistics

Grouping variable(s) for various functions

Combine documents in a dfm by a grouping variable

Replace features in dfm

Sort a dfm by frequency of one or more margins

summary.textmodel_wordfish

summary method for textmodel_wordfish

Function to assign multiple slots to a S4 object

print.summary.textmodel

print method for summary.textmodel

Get or set the corpus settings

Coerce a dfm to a matrix or data.frame

Combine dfm objects by Rows or Columns

dfm_split_hyphenated_features

Split a dfm's hyphenated features into constituent parts

Convert the case of character objects

corpus_trimsentences

Remove sentences based on their token lengths or a pattern match

Check if patterns contains glob wildcard

Utility function to create a object with new set of attributes

Return the first or last part of a dfm

Virtual class "fcm" for a feature co-occurrence matrix The fcm class of object is a special type of fcm object with additional slots, described below.

Converts a Matrix to a fcm

Return the first or last part of a corpus

Simpler and faster version of expand.grid() in base package

Correspondence analysis of a document-feature matrix

summary_character

Summary statistics on a character vector

textmodel_lsa-postestimation

Post-estimations methods for textmodel_lsa

Plot the dispersion of key word(s)

Check if a glob pattern is indexed by index_types

Get or assign corpus texts

textstat_dist_old

Similarity and distance computation between documents or features

predict.textmodel_wordfish

Prediction from a textmodel_wordfish method

print.textmodel_wordfish

print method for a wordfish model

nest_dictionary

Utility function to generate a nested list

merge_dictionary_values

Internal function to merge values of duplicated keys

quanteda-package

An R package for the quantitative analysis of textual data

predict.textmodel_wordscores

Predict textmodel_wordscores

Defunct form of nfeat

Apply a dictionary to a dfm

Compute keyness (internal functions)

Count syllables in a text

tokens_serialize

Function to serialized list-of-character tokens

deprecated name for dfm_weight

Split tokens by a separator pattern

friendly_class_undefined_message

Print friendly object class not defined message

Select features from a dfm or fcm

format_sparsity

format a sparsity value for printing

Get or set document names

Compute the (weighted) document frequency of a feature

Randomly sample documents or features from a dfm

Count the Scrabble letter values of text

Convert a dfm to an lsa "textmatrix"

Count the number of sentences

Count the number of tokens or types

Pattern for feature, token and keyword matching

Deprecated name for nscrabble

Objects exported from other packages

Select types without performing slow regex search

Convert regex and glob patterns to type IDs or fixed patterns

remove_empty_keys

Utility function to remove empty keys

tokens_wordstem

Stem the terms in an object

[Experimental] Change direction of words in tokens

quanteda_options

Get or set package options for quanteda

Declare a compound character to be a sequence of separate pattern matches

Convert various input as pattern to a vector used in tokens_select, tokens_compound and kwic.

Recombine a dfm or fcm by combining identical dimension elements

set_dfm_dimnames<-

Internal functions to set dimnames

Internal function for select_types to search the index using fastmatch.

read_dict_functions

Internal functions to import dictionary files

Set values to a dfm's S4 slots

lowercase_dictionary_values

Internal function to lowercase dictionary values

Create a dictionary

dictionary2-class

Coerce a dictionary object into a list

Weight a dfm by tf-idf

Extract a subset of a dfm

Summarize a corpus

Set values to a fcm's S4 slots

textmodel_affinity

Class affinity maximum likelihood text scaling model

textmodel_affinity-internal

Internal methods for textmodel_affinity

Internal function for special handling of multi-word dictionary values

summary.textmodel_nb

summary method for textmodel_nb objects

summary.character

summary.character method to override the network::summary.character()

textplot_influence

Influence plot for text scaling models

textmodel_wordshoal

Wordshoal text model (redirect)

tokens_compound

Convert token sequences into compound tokens

Segment tokens object by chunks of a given size

Locate keywords-in-context

head.textstat_proxy

Return the first or last part of a textstat_proxy object

influence.predict.textmodel_affinity

Compute feature influence from a predicted textmodel_affinity object

list2dictionary

Internal function to convert a list to a dictionary

Count the number of documents or features

Get or set document-level meta-data

Converts a Matrix to a dfm

Return an error message

Get or set corpus metadata

textplot_keyness

Plot word keyness

textplot_network

Plot a network of feature co-occurrences

tokens_recompile

recompile a serialized tokens object

Create ngrams and skipgrams from tokens

[Experimental] Compute document/feature proximity

textstat_entropy

Compute entropy of documents or features

textstat_readability

Calculate readability

textstat_collocations

Identify and score multi-word expressions

Tokenize a set of texts

textstat_frequency

Tabulate feature frequencies

textstat_keyness

Calculate keyness statistics

Deprecated form of dfm_tfidf

print.coefficients_textmodel

Print methods for textmodel features estimates This is a helper function used in print.summary.textmodel.

Recombine documents tokens by groups

Replace tokens in a tokens object

print.dist_selection

Print a dist_selection object

Print a dfm object

Print a phrase object

textmodel_wordscores

Wordscores text model

Extract a subset of a tokens

textmodel_wordfish

Wordfish text model

Randomly sample documents from a tokens object

Convert the case of tokens

Raise warning of unused dots

Apply a dictionary to a tokens object

replace_dictionary_values

Internal function to replace dictionary values

Internal function for textplot_wordcloud

Pattern matching using valuetype

wordcloud_comparison

Internal function for textplot_wordcloud

Naive Bayes classifier for texts

Extensions for and from spacy_parse objects

Latent Semantic Analysis

Compute the sparsity of a document-feature matrix

Sample a vector by a group

textplot_wordcloud

Plot features as a wordcloud

textplot_scale1d

Plot a fitted scaling model

Identify the most frequent features in a dfm

Get word types from a tokens object

textstat_lexdiv

Calculate lexical diversity

textstat_proxy-class

textstat_simil/dist classes

Unlist a list of integer vectors safely

Select or remove tokens from a tokens object

Similarity and distance computation between documents or features

Segment tokens object by patterns

textstat_select

Select rows of textstat objects by glob, regex or fixed patterns

unlist_character

Unlist a list of character vectors safely