A fast, flexible, and comprehensive framework for
quantitative text analysis in R. Provides functionality for corpus management,
creating and manipulating tokens and n-grams, exploring keywords in context,
forming and manipulating sparse matrices
of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and
distances, applying content dictionaries, applying supervised and unsupervised machine learning,
visually representing text and text analyses, and more.
| Version: |
4.3.1 |
| Depends: |
R (≥ 4.1.0), methods |
| Imports: |
fastmatch, jsonlite, lifecycle, magrittr, Matrix (≥ 1.5-0), Rcpp (≥ 0.12.12), SnowballC, stopwords, stringi, xml2, yaml |
| LinkingTo: |
Rcpp |
| Suggests: |
rmarkdown, spelling, testthat, formatR, tm (≥ 0.6), knitr, lsa, rlang, slam |
| Enhances: |
dplyr, lda, purrr, spacyr, stm, text2vec, tibble, tidytext, tokenizers, topicmodels |
| Published: |
2025-07-10 |
| DOI: |
10.32614/CRAN.package.quanteda |
| Author: |
Kenneth Benoit 
[cre, aut, cph],
Kohei Watanabe
[aut],
Haiyan Wang [aut],
Paul Nulty [aut],
Adam Obeng [aut],
Stefan Müller
[aut],
Akitaka Matsuo
[aut],
William Lowe
[aut],
Christian Müller [ctb],
Olivier Delmarcelle
[ctb],
European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS) |
| Maintainer: |
Kenneth Benoit <kbenoit at lse.ac.uk> |
| BugReports: |
https://github.com/quanteda/quanteda/issues |
| License: |
GPL-3 |
| URL: |
https://quanteda.io |
| NeedsCompilation: |
yes |
| Language: |
en-GB |
| Citation: |
quanteda citation info |
| Materials: |
README, NEWS |
| In views: |
NaturalLanguageProcessing |
| CRAN checks: |
quanteda results |