Package: quanteda.textmodels 0.9.10

Kenneth Benoit

quanteda.textmodels: Scaling Models and Classifiers for Textual Data

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) <doi:10.1017/S0003055403000698>, 'Wordscores' model, the Perry and 'Benoit' (2017) <doi:10.48550/arXiv.1710.08963> class affinity scaling model, and the 'Slapin' and 'Proksch' (2008) <doi:10.1111/j.1540-5907.2008.00338.x> '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.

Authors:Kenneth Benoit [cre, aut, cph], Kohei Watanabe [aut], Haiyan Wang [aut], Patrick O. Perry [aut], Benjamin Lauderdale [aut], Johannes Gruber [aut], William Lowe [aut], Vikas Sindhwani [cph], European Research Council [fnd]

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quanteda.textmodels.pdf |quanteda.textmodels.html✨
quanteda.textmodels/json (API)
NEWS

# Install 'quanteda.textmodels' in R:
install.packages('quanteda.textmodels', repos = 'https://cloud.r-project.org')

Bug tracker:https://github.com/quanteda/quanteda.textmodels/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

4.72 score 2.6k downloads 15 mentions 16 exports 26 dependencies

Last updated 2 months agofrom:862a9c0fc5. Checks:2 OK, 1 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 13 2025
R-4.5-linux-x86_64OKMar 13 2025
R-4.4-linux-x86_64NOTEMar 13 2025

Exports:affinityas.coefficients_textmodelas.statistics_textmodelas.summary.textmodelcoefficients.textmodel_cacoefficients.textmodel_lsacoefficients.textmodel_wordfishtextmodel_affinitytextmodel_catextmodel_lrtextmodel_lsatextmodel_nbtextmodel_svmlintextmodel_wordfishtextmodel_wordscorestextplot_influence

Dependencies:clicodetoolsfastmatchforeachglmnetglueISOcodesiteratorsjsonlitelatticelifecyclemagrittrMatrixquantedaRcppRcppArmadilloRcppEigenrlangRSpectrashapeSnowballCstopwordsstringisurvivalxml2yaml

textmodel Performance Comparisons

Kenneth Benoit

Rendered fromtextmodel_performance.Rmdusingknitr::rmarkdownon Mar 13 2025.

Last update: 2024-04-12
Started: 2020-03-13

Citation

To cite package ‘quanteda.textmodels’ in publications use:

Benoit K, Watanabe K, Wang H, Perry P, Lauderdale B, Gruber J, Lowe W (2025). quanteda.textmodels: Scaling Models and Classifiers for Textual Data. R package version 0.9.10, https://CRAN.R-project.org/package=quanteda.textmodels.

Corresponding BibTeX entry: 

  @Manual{,
    title = {quanteda.textmodels: Scaling Models and Classifiers for
      Textual Data},
    author = {Kenneth Benoit and Kohei Watanabe and Haiyan Wang and
      Patrick O. Perry and Benjamin Lauderdale and Johannes Gruber and
      William Lowe},
    year = {2025},
    note = {R package version 0.9.10},
    url = {https://CRAN.R-project.org/package=quanteda.textmodels},
  }

Readme and manuals

quanteda.textmodels

About

An R package adding text scaling models and classifiers for quanteda. Prior to quanteda v2, many of these were part of that package. Early development was supported by the European Research Council grant ERC-2011-StG 283794-QUANTESS.

For more details, see https://quanteda.io.

How to Install

You can install it via the normal way from CRAN, using your R GUI or

install.packages("quanteda.textmodels")

Or for the latest development version:

# devtools package required to install quanteda from Github 
remotes::install_github("quanteda/quanteda.textmodels")

Because this compiles some C++ and Fortran source code, you will need to have installed the appropriate compilers. On Windows platform, this means the Rtools software available from CRAN, or the macOS tools from macOS tools, including namely the Clang 6.x compiler and the GNU Fortran compiler (as quanteda requires gfortran to build). If you are still getting errors related to gfortran, follow the fixes here.

How to cite

Benoit, Kenneth, Kohei Watanabe, Haiyan Wang, Paul Nulty, Adam Obeng, Stefan Müller, and Akitaka Matsuo. (2018) “quanteda: An R package for the quantitative analysis of textual data”. Journal of Open Source Software. 3(30), 774. https://doi.org/10.21105/joss.00774.

For a BibTeX entry, use the output from citation(package = "quanteda").

Leaving Feedback

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Contributing

Contributions in the form of feedback, comments, code, and bug reports are most welcome. How to contribute: