R: quanteda.textmodels: Scaling Models and Classifiers for...

textmodels {quanteda.textmodels} | R Documentation

## quanteda.textmodels: Scaling Models and Classifiers for Textual Data

### 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) <doi:10.1017/S0003055403000698>, 'Wordscores' model, Perry and 'Benoit's' (2017) <arXiv:1710.08963> class affinity scaling model, and 'Slapin' and 'Proksch's' (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.

### Author(s)

Maintainer: Kenneth Benoit kbenoit@lse.ac.uk (ORCID) [copyright holder]

Authors:

- Kohei Watanabe watanabe.kohei@gmail.com (ORCID)

- Haiyan Wang whyinsa@yahoo.com (ORCID)

- Patrick O. Perry patperry@gmail.com (ORCID)

- Benjamin Lauderdale b.e.lauderdale@lse.ac.uk (ORCID)

- Johannes Gruber j.gruber.1@research.gla.ac.uk (ORCID)

- William Lowe lowe@hertie-school.org (ORCID)

Other contributors:

- Vikas Sindhwani vikas.sindhwani@gmail.com (authored svmlin C++ source code) [copyright holder]

- European Research Council (ERC-2011-StG 283794-QUANTESS) [funder]

### See Also

Useful links:

- https://github.com/quanteda/quanteda.textmodels

[Package quanteda.textmodels version 0.9.4 Index]