data.table, R6, xml2, stringi, curl, RcppCWB (>= 0.2.8),
pbapply, methods, usethis, rstudioapi, jsonlite, RCurl
tm (>= 0.7.3), knitr, tokenizers (>= 0.2.1), tidytext,
SnowballC, janeaustenr, devtools, polmineR, NLP, testthat
'CorpusData.R' 'corpus.R' 'cwb.R' 'cwbtools.R' 'directories.R'
'encoding.R' 'ner.R' 'p_attribute.R' 'pkg.R' 'registry_file.R'
's_attribute.R' 'zenodo.R'

Tools to Create, Modify and Manage 'CWB' Corpora
data.table, R6, xml2, stringi, curl, RcppCWB (>= 0.2.8),
pbapply, methods, cli, jsonlite, RCurl, rstudioapi, zen4R
tm (>= 0.7.3), knitr, tokenizers (>= 0.2.1), tidytext,
SnowballC, janeaustenr, devtools, polmineR, NLP, testthat,
usethis, rmarkdown
'CorpusData.R' 'corpus.R' 'cwb.R' 'cwbtools.R' 'directories.R'
'encoding.R' 'ner.R' 'p_attribute.R' 'pkg.R' 'registry_file.R'
's_attribute.R'

tm (>= 0.7.3), knitr, tokenizers (>= 0.2.1), tidytext,
SnowballC, janeaustenr, devtools, NLP, testthat, usethis,
rmarkdown

data.table, R6, xml2, stringi, curl, RcppCWB (>= 0.2.8),
pbapply, methods, tools, cli, jsonlite, httr, rstudioapi, zen4R
tm (>= 0.7.3), knitr, tokenizers (>= 0.2.1), tidytext,
SnowballC, janeaustenr, devtools, NLP, testthat, usethis,
rmarkdown, openNLP, aws.s3

tm (>= 0.7.3), knitr, tokenizers (>= 0.2.1), tidytext,
SnowballC, janeaustenr, NLP, testthat, rmarkdown, openNLP,
aws.s3

data.table, R6, xml2, stringi, curl, RcppCWB (>= 0.2.8),
pbapply, methods, tools, cli, jsonlite, httr, rstudioapi,
zen4R, lifecycle, fs
tm (>= 0.7.3), knitr, markdown, tokenizers (>= 0.2.1),
tidytext, SnowballC, janeaustenr, NLP, testthat, rmarkdown,
openNLP, aws.s3
'CorpusData.R' 'corpus.R' 'cwb.R' 'cwbtools.R' 'directories.R'
'encoding.R' 'ner.R' 'p_attribute.R' 'pkg.R' 'registry_file.R'
's_attribute.R' 'vrt.R'

c(person("Andreas", "Blaette", role = c("aut", "cre"), email = "andreas.blaette@uni-due.de"),
person("Christoph", "Leonhardt", role = "aut", email = "christoph.leonhardt@uni-due.de")
)
The 'Corpus Workbench' ('CWB', <https://cwb.sourceforge.io/>) offers a classic and mature
approach for working with large, linguistically and structurally annotated corpora. The 'CWB'
is memory efficient and its design makes running queries fast (Evert and Hardie 2011,
<http://www.stefan-evert.de/PUB/EvertHardie2011.pdf>). The 'cwbtools' package offers
pure R tools to create indexed corpus files as well as high-level wrappers for the original C
implementation of CWB as exposed by the 'RcppCWB' package
<https://CRAN.R-project.org/package=RcppCWB>. Additional functionality to add and
modify annotations of corpora from within R makes working with CWB indexed corpora
much more flexible and convenient. The 'cwbtools' package in combination with the R packages
'RcppCWB' (<https://CRAN.R-project.org/package=RcppCWB>) and 'polmineR'
(<https://CRAN.R-project.org/package=polmineR>) offers a lightweight infrastructure
to support the combination of quantitative and qualitative approaches for working
with textual data.
data.table, R6, xml2, stringi, curl, RcppCWB (>= 0.5.2),
pbapply, methods, tools, cli, jsonlite, httr, rstudioapi,
zen4R, lifecycle, fs
'CorpusData.R' 'corpus.R' 'cwb.R' 'cwbtools.R' 'directories.R'
'encoding.R' 'ner.R' 'p_attribute.R' 'pkg.R' 'registry_file.R'
's_attribute.R' 'vrt.R' 'zenodo.R'
Andreas Blaette [aut, cre],
Christoph Leonhardt [aut]