text: Analyses of Text using Natural Language Processing and Machine Learning

Transforms text variables to word embeddings; where the word embeddings are used to statistically test the mean difference between set of texts, compute semantic similarity scores between texts, predict numerical variables, and visual statistically significant words according to various dimensions etc. For more information see <https://www.r-text.org>.

Version: 0.9.10
Depends: R (≥ 4.00)
Imports: dplyr, tokenizers, tibble, stringr, tidyr, ggplot2, ggrepel, cowplot, rlang, purrr, magrittr, parsnip, recipes, rsample, reticulate, tune, workflows, yardstick, future, furrr
Suggests: knitr, rmarkdown, testthat, rio, glmnet, randomForest, covr, xml2, ranger
Published: 2020-12-14
Author: Oscar Kjell ORCID iD [aut, cre], Salvatore Giorgi ORCID iD [aut], Andrew Schwartz ORCID iD [aut]
Maintainer: Oscar Kjell <oscar.kjell at psy.lu.se>
BugReports: https://github.com/OscarKjell/text/issues/
License: GPL-3
URL: https://r-text.org/, https://github.com/OscarKjell/text/
NeedsCompilation: no
SystemRequirements: Python (>= 3.6.0)
Citation: text citation info
Materials: README NEWS
CRAN checks: text results

Downloads:

Reference manual: text.pdf
Vignettes: Computer_Capacity
Extended_Installation_Guide
Pre-registration
Removing_Cache_Files
Word_Embeddings
text
Package source: text_0.9.10.tar.gz
Windows binaries: r-devel: text_0.9.10.zip, r-release: text_0.9.10.zip, r-oldrel: text_0.9.10.zip
macOS binaries: r-release (arm64): text_0.9.10.tgz, r-release (x86_64): text_0.9.10.tgz, r-oldrel: text_0.9.10.tgz
Old sources: text archive

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