A fast, flexible, and comprehensive framework for
quantitative text analysis in R. Provides functionality for corpus management,
creating and manipulating tokens and ngrams, 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: |
3.2.2 |
Depends: |
R (≥ 3.5.0), methods |
Imports: |
fastmatch, magrittr, Matrix (≥ 1.2), Rcpp (≥ 0.12.12), RcppParallel, SnowballC, stopwords, stringi, xml2, yaml |
LinkingTo: |
Rcpp, RcppParallel, RcppArmadillo (≥ 0.7.600.1.0) |
Suggests: |
rmarkdown, spelling, testthat, formatR, tm (≥ 0.6), tokenizers, knitr, lda, lsa, dplyr, purrr, quanteda.textmodels, quanteda.textstats, quanteda.textplots, RColorBrewer, slam, spacyr, stm, text2vec, topicmodels, jsonlite, quanteda, tibble, tidytext, xtable, ggplot2 |
Published: |
2022-08-09 |
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],
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 |
SystemRequirements: |
C++11 |
Language: |
en-GB |
Citation: |
quanteda citation info |
Materials: |
README NEWS |
In views: |
NaturalLanguageProcessing |
CRAN checks: |
quanteda results |