Scaling Models and Classifiers for Textual Data R package quanteda.textmodels version 0.9.10 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. Software Depends: R (>= 3.1.0), methods Imports: glmnet, Matrix (>= 1.2), quanteda (>= 4.0.0), RSpectra, Rcpp (>= 0.12.12), stringi LinkingTo: Rcpp, RcppArmadillo (>= 0.7.600.1.0), quanteda Suggests: ca, covr, fastNaiveBayes, knitr, lsa, microbenchmark, naivebayes, quanteda.textplots, spelling, testthat, rmarkdown Kenneth Benoit <kbenoit@quanteda.org> Comprehensive R Archive Network (CRAN) Kenneth Benoit [cre, aut, cph] (ORCID: <https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (ORCID: <https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (ORCID: <https://orcid.org/0000-0003-4992-4311>), Patrick O. Perry [aut] (ORCID: <https://orcid.org/0000-0001-7460-127X>), Benjamin Lauderdale [aut] (ORCID: <https://orcid.org/0000-0003-3090-0969>), Johannes Gruber [aut] (ORCID: <https://orcid.org/0000-0001-9177-1772>), William Lowe [aut] (ORCID: <https://orcid.org/0000-0002-1549-6163>), Vikas Sindhwani [cph] (authored svmlin C++ source code), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS) GPL-3 2025-02-10 application/tgz https://CRAN.R-project.org/package=quanteda.textmodels doi:10.32614/CRAN.package.quanteda.textmodels en-GB