quanteda is an R package for managing and analyzing textual data developed by Kenneth Benoit, Kohei Watanabe, and other contributors. Its initial development was supported by the European Research Council grant ERC-2011-StG 283794-QUANTESS.
The package is designed for R users needing to apply natural language processing to texts, from documents to final analysis. Its capabilities match or exceed those provided in many end-user software applications, many of which are expensive and not open source. The package is therefore of great benefit to researchers, students, and other analysts with fewer financial resources. While using quanteda requires R programming knowledge, its API is designed to enable powerful, efficient analysis with a minimum of steps. By emphasizing consistent design, furthermore, quanteda lowers the barriers to learning and using NLP and quantitative text analysis even for proficient R programmers.
quanteda 3.0 is a major release that improves functionality, completes the modularisation of the package begun in v2.0, further improves function consistency by removing previously deprecated functions, and enhances workflow stability and consistency by deprecating some shortcut steps built into some functions.
See https://github.com/quanteda/quanteda/blob/master/NEWS.md#quanteda-30 for a full list of the changes.
As of v3.0, we have continued our trend of splitting quanteda into modular packages. These are now the following:
- quanteda: contains all of the core natural language processing and textual data management functions
- quanteda.textmodels: contains all of the text models and
supporting functions, namely the
textmodel_*()functions. This was split from the main package with the v2 release - quanteda.textstats: statistics for textual data, namely the
textstat_*()functions, split with the v3 release - quanteda.textplots: plots for textual data, namely the
textplot_*()functions, split with the v3 release
We are working on additional package releases, available in the meantime from our GitHub pages:
- quanteda.sentiment: Functions and lexicons for sentiment analysis using dictionaries
- quanteda.tidy: Extensions for manipulating document variables in core quanteda objects using your favourite tidyverse functions
and more to come.
The normal way from CRAN, using your R GUI or
install.packages("quanteda")
Or for the latest development version:
# devtools package required to install quanteda from Github
remotes::install_github("quanteda/quanteda")
Because this compiles some C++ and Fortran source code, you will need to have installed the appropriate compilers to build the development version.
See the quick start guide to learn how to use quanteda.
- Read out documentation at https://quanteda.io.
- Submit a question on the quanteda channel on StackOverflow.
- See our tutorial site.
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").
If you like quanteda, please consider leaving feedback or a testimonial here.
Contributions in the form of feedback, comments, code, and bug reports are most welcome. How to contribute:
- Fork the source code, modify, and issue a pull request through the project GitHub page. See our Contributor Code of Conduct and the all-important quanteda Style Guide.
- Issues, bug reports, and wish lists: File a GitHub issue.
- Contact the maintainer by email.