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quanteda.textmodels  

Scaling Models and Classifiers for Textual Data
View on CRAN: Click here


Download and install quanteda.textmodels package within the R console
Install from CRAN:
install.packages("quanteda.textmodels")

Install from Github:
library("remotes")
install_github("cran/quanteda.textmodels")

Install by package version:
library("remotes")
install_version("quanteda.textmodels", "0.9.10")



Attach the package and use:
library("quanteda.textmodels")
Maintained by
Kenneth Benoit
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-02-26
Latest Update: 2025-02-10
Description:
Scaling models and classifiers for sparse matrix objects representing textual data in the form of a document-feature matrix. Includes original implementations of 'Laver', 'Benoit', and Garry's (2003) , 'Wordscores' model, the Perry and 'Benoit' (2017) class affinity scaling model, and the 'Slapin' and 'Proksch' (2008) 'wordfish' model, as well as methods for correspondence analysis, latent semantic analysis, and fast Naive Bayes and linear 'SVMs' specially designed for sparse textual data.
How to cite:
Kenneth Benoit (2020). quanteda.textmodels: Scaling Models and Classifiers for Textual Data. R package version 0.9.10, https://cran.r-project.org/web/packages/quanteda.textmodels. Accessed 05 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:46), 0.9.0 (2020-02-26 16:50), 0.9.1 (2020-03-13 11:00), 0.9.2 (2020-12-11 12:10), 0.9.3 (2021-03-07 23:40), 0.9.4 (2021-04-06 09:30), 0.9.5-1 (2022-10-05 00:40), 0.9.5 (2022-08-29 17:30), 0.9.6 (2023-03-22 10:20), 0.9.7 (2024-04-11 10:10), 0.9.8 (2024-08-29 09:30), 0.9.9 (2024-09-03 18:00)
Other packages that cited quanteda.textmodels R package
View quanteda.textmodels citation profile
Other R packages that quanteda.textmodels depends, imports, suggests or enhances
Complete documentation for quanteda.textmodels
Functions, R codes and Examples using the quanteda.textmodels R package
Some associated functions: affinity . as.coefficients_textmodel . as.matrix.csr.dfm . as.statistics_textmodel . as.summary.textmodel . coef.textmodel_ca . data_corpus_EPcoaldebate . data_corpus_dailnoconf1991 . data_corpus_irishbudget2010 . data_corpus_moviereviews . force_conformance . influence.predict.textmodel_affinity . predict.textmodel_affinity . predict.textmodel_lr . predict.textmodel_nb . predict.textmodel_svm . predict.textmodel_svmlin . predict.textmodel_wordfish . predict.textmodel_wordscores . print.coefficients_textmodel . print.statistics_textmodel . print.summary.textmodel . print.textmodel_wordfish . summary.textmodel_lr . summary.textmodel_nb . summary.textmodel_svm . summary.textmodel_svmlin . summary.textmodel_wordfish . textmodel_affinity-internal . textmodel_affinity . textmodel_ca . textmodel_lr . textmodel_lsa-postestimation . textmodel_lsa . textmodel_nb . textmodel_svm . textmodel_svmlin . textmodel_wordfish . textmodel_wordscores . textmodels . textplot_influence . 
Some associated R codes: RcppExports.R . data-documentation.R . quanteda.textmodels-package.R . textmodel-methods.R . textmodel_affinity.R . textmodel_ca.R . textmodel_lr.R . textmodel_lsa.R . textmodel_nb.R . textmodel_svm.R . textmodel_svmlin.R . textmodel_wordfish.R . textmodel_wordscores.R . textplot_influence.R . utils.R .  Full quanteda.textmodels package functions and examples
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