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

14,329

Version

1.4.1

License

GPL-3

Maintainer

Kenneth Benoit

Last Published

February 26th, 2019

Functions in quanteda (1.4.1)

as.list.dist_selection

Coerce a dist_selection object into a list

Convert a dfm to a non-quanteda format

Coercion, checking, and combining functions for tokens objects

as.summary.textmodel

Assign the summary.textmodel class to a list

data_dictionary_LSD2015

Lexicoder Sentiment Dictionary (2015)

data_dfm_lbgexample

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

Select features from a dfm or fcm

convert-wrappers

Convenience wrappers for dfm convert

Convert quanteda dictionary objects to the YAML format

coerce a compressed corpus to a standard corpus

redefinition of network::as.network()

Convert an fcm to an igraph object

Coerce a dist object into a list

Convert the case of character objects

Coerce a dfm to a matrix or data.frame

Bootstrap a dfm

Function extending base::attributes()

as.matrix.dist_selection

Coerce a dist_selection object to a matrix

as.matrix.simil

Coerce a simil object into a matrix

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

as.statistics_textmodel

Coerce various objects to statistics_textmodel

coef.textmodel_ca

Extract model coefficients from a fitted textmodel_ca object

compute_lexdiv_stats

Compute lexical diversity from a dfm or tokens

Sort a dfm by frequency of one or more margins

Combine dfm objects by Rows or Columns

Remove sentences based on their token lengths or a pattern match

Compute the Mean Segmental Type-Token Ratio (MSTTR)

Base method extensions for corpus objects

Construct a corpus object

Internal data sets

data_char_sampletext

A paragraph of text for testing various text-based functions

Recast the document units of a corpus

Segment texts on a pattern match

corpus_trimsentences

Remove sentences based on their token lengths or a pattern match

Check if font is available on the system

Utility function to create a object with new set of attributes

data-deprecated

Datasets with deprecated or defunct names

Extract a subset of a corpus

data_corpus_irishbudget2010

Irish budget speeches from 2010

data_corpus_inaugural

US presidential inaugural address texts

Randomly sample documents from a corpus

data_char_ukimmig2010

Immigration-related sections of 2010 UK party manifestos

Recombine a dfm or fcm by combining identical dimension elements

Create a document-feature matrix

Get the feature labels from a dfm

Apply a dictionary to a dfm

flatten_dictionary

Flatten a hierarchical dictionary into a list of character vectors

Match the feature set of a dfm to given feature names

data_corpus_dailnoconf1991

Confidence debate from 1991 Irish Parliament

Combine documents in a dfm by a grouping variable

Convert a dfm to an lsa "textmatrix"

dfm_split_hyphenated_features

Split a dfm's hyphenated features into constituent parts

influence.predict.textmodel_affinity

Compute feature influence from a predicted textmodel_affinity object

Virtual class "dfm" for a document-feature matrix

Internal functions for dfm objects

Replace features in dfm

Extract a subset of a dfm

Check if patterns contains glob wildcard

Randomly sample documents or features from a dfm

dictionary2-class

Coerce a dictionary object into a list

Trim a dfm using frequency threshold-based feature selection

Create a dictionary

merge_dictionary_values

Internal function to merge values of duplicated keys

Weight the feature frequencies in a dfm

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

Compute the (weighted) document frequency of a feature

Return an error message

Get or set document names

Weight a dfm by tf-idf

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.

Internal function for select_types() to escape regular expressions

Get or set document-level variables

format_sparsity

format a sparsity value for printing

friendly_class_undefined_message

Print friendly object class not defined message

Convert the case of the features of a dfm and combine

Create a feature co-occurrence matrix

list2dictionary

Internal function to convert a list to a dictionary

Sort an fcm in alphabetical order of the features

Count the number of documents or features

nest_dictionary

Utility function to generate a nested list

lowercase_dictionary_values

Internal function to lowercase dictionary values

Get or set corpus metadata

Return the first or last part of a corpus

Check if a glob pattern is indexed by index_types

predict.textmodel_nb

Prediction from a fitted textmodel_nb object

Return the first or last part of a dfm

predict.textmodel_wordfish

Prediction from a textmodel_wordfish method

Get or set document-level meta-data

Count the number of tokens or types

generate_groups

Generate a grouping vector from docvars

Grouping variable(s) for various functions

Converts a Matrix to a dfm

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

Count the number of sentences

Converts a Matrix to a fcm

Compute keyness (internal functions)

Count syllables in a text

predict.textmodel_wordscores

Predict textmodel_wordscores

print.summary.textmodel

print method for summary.textmodel

print.textmodel_wordfish

print method for a wordfish model

Locate keywords-in-context

Defunct form of nfeat

print.coefficients_textmodel

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

Count the Scrabble letter values of text

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

Extensions for and from spacy_parse objects

predict.textmodel_affinity

Prediction for a fitted affinity textmodel

Pattern for feature, token and keyword matching

Print a dfm object

read_dict_lexicoder

Import a Lexicoder dictionary

Compute the sparsity of a document-feature matrix

print.dist_selection

Print a dist_selection object

Import a LIWC-formatted dictionary

quanteda-package

An R package for the quantitative analysis of textual data

Objects exported from other packages

textmodel_wordshoal

Wordshoal text model (redirect)

Convert regex and glob patterns to type IDs or fixed patterns

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

remove_empty_keys

Utility function to remove empty keys

Set values to a dfm's S4 slots

Set values to a fcm's S4 slots

Internal function for select_types to search the index using fastmatch.

textplot_influence

Influence plot for text scaling models

textmodel_affinity-internal

Internal methods for textmodel_affinity

textmodel_affinity

Class affinity maximum likelihood text scaling model

Get or set the corpus settings

Function to assign multiple slots to a S4 object

Latent Semantic Analysis

quanteda_options

Get or set package options for quanteda

Summarize a corpus

Naive Bayes classifier for texts

summary.textmodel_nb

summary method for textmodel_nb objects

set_dfm_dimnames<-

Internal functions to set dimnames

Correspondence analysis of a document-feature matrix

summary.textmodel_wordfish

summary method for textmodel_wordfish

summary_character

Summary statistics on a character vector

textstat_lexdiv

Calculate lexical diversity

Print a phrase object

Plot the dispersion of key word(s)

Deprecated name for nscrabble

textmodel_lsa-postestimation

Post-estimations methods for textmodel_lsa

print.statistics_textmodel

Implements print methods for textmodel_statistics

textplot_keyness

Plot word keyness

textplot_scale1d

Plot a fitted scaling model

Get or assign corpus texts

textplot_wordcloud

Plot features as a wordcloud

textplot_network

Plot a network of feature co-occurrences

[Experimental] Compute document/feature proximity

textstat_collocations

Identify and score multi-word expressions

Select types without performing slow regex search

tokens_compound

Convert token sequences into compound tokens

read_dict_wordstat

Import a Wordstat dictionary

deprecated name for dfm_weight

Recombine documents tokens by groups

Deprecated form of dfm_tfidf

textstat_entropy

Compute entropy of documents or features

read_dict_yoshikoder

Import a Yoshikoder dictionary file.

replace_dictionary_values

Internal function to replace dictionary values

Sample a vector by a group

Randomly sample documents from a tokens object

Internal function for special handling of multi-word dictionary values

Segment tokens object by patterns

tokens_recompile

recompile a serialized tokens object

Replace tokens in a tokens object

wordcloud_comparison

Internal function for textplot_wordcloud

summary.character

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

textstat_readability

Calculate readability

textstat_select

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

Tokenize a set of texts

Segment tokens object by chunks of a given size

textmodel_wordfish

Wordfish text model

textmodel_wordscores

Wordscores text model

Pattern matching using valuetype

Internal function for textplot_wordcloud

textstat_frequency

Tabulate feature frequencies

textstat_keyness

Calculate keyness statistics

Similarity and distance computation between documents or features

textstat_dist_old

Similarity and distance computation between documents or features

Select or remove tokens from a tokens object

tokens_serialize

Function to serialized list-of-character tokens

Apply a dictionary to a tokens object

Get word types from a tokens object

Raise warning of unused dots

Create ngrams and skipgrams from tokens

Convert the case of tokens

Split tokens by a separator pattern

[Experimental] Change direction of words in tokens

Extract a subset of a tokens

tokens_wordstem

Stem the terms in an object

Identify the most frequent features in a dfm

as.corpus.corpuszip

Coerce a compressed corpus to a standard corpus

Coercion and checking functions for dfm objects

Internal function to fit the likelihood scaling mixture model.

as.coefficients_textmodel

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

View methods for quanteda

Coercion functions for fcm objects

as.data.frame.dfm

Convert a dfm to a data.frame

Coerce a dist into a dist

Coercion and checking functions for dictionary objects