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index.Rmd
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index.Rmd
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---
output: md_document
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "##",
fig.path = "man/images/"
)
```
# quanteda: Quantitative Analysis of Textual Data
**quanteda** is an R package for managing and analyzing text, created and maintained by [Kenneth Benoit](https://kenbenoit.net) and [Kohei Watanabe](https://blog.koheiw.net/). Its creation was funded by the European Research Council grant ERC-2011-StG 283794-QUANTESS and its continued development is supported by the [Quanteda Initiative CIC](https://quanteda.org).
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** version 4
The **quanteda** 4.0 is a major release that improves functionality and performance and further improves function consistency by removing previously deprecated functions. It also includes significant new tokeniser rules that makes the default tokeniser smarter than ever before, with new Unicode and ICU-compliant rules that enable it to work more consistently with even more languages.
We describe more fully these significant changes in:
* an [article about the new external pointer tokens objects](https://quanteda.io/articles/pkgdown/tokens_xptr.html);
* an [article showing performance benchmarks](https://quanteda.io/articles/pkgdown/benchmarks_xptr.html) for the new external pointer tokens objects, as well as some of the tokeniser improvements in v4; and
* the [changelog for v4](https://github.com/quanteda/quanteda/blob/master/NEWS.md#quanteda-40) a full listing of the changes, improvements, and deprecations in v4.
## The **quanteda** family of packages
We completed the trend of splitting **quanteda** into modular packages with the release of v3. The quanteda family of packages includes 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
## How To...
### Install (binaries) from CRAN
The normal way from CRAN, using your R GUI or
```{r eval = FALSE}
install.packages("quanteda")
```
**(New for quanteda v4.0)** For Linux users: Because all installations on Linux are compiled, Linux users will first need to install the Intel oneAPI Threading Building Blocks for parallel computing for installation to work.
To install TBB on Linux:
```{bash eval = FALSE}
# Fedora, CentOS, RHEL
sudo yum install tbb-devel
# Debian and Ubuntu
sudo apt install libtbb-dev
```
Windows or macOS users do not have to install TBB or any other packages to enable parallel computing when installing **quanteda** from CRAN.
### Compile from source (macOS and Windows)
Because this compiles some C++ and Fortran source code, you will need to have installed the appropriate compilers to build the development version.
You will also need to install TBB:
**macOS:**
First, you will need to install XCode command line tools.
```{bash eval = FALSE}
xcode-select --install
```
Then install the TBB libraries and the pkg-config utility: (after installing [Homebrew](https://brew.sh)):
```{bash eval = FALSE}
brew install tbb pkg-config
```
Finally, you will need to install [gfortran](https://github.com/fxcoudert/gfortran-for-macOS/releases).
**Windows:**
Install [RTools](https://cran.r-project.org/bin/windows/Rtools/), which includes the TBB libraries.
### Use **quanteda**
See the [quick start guide](https://quanteda.io/articles/quickstart.html) to learn how to use **quanteda**.
### Get Help
* Read out documentation at https://quanteda.io.
* Submit a question on the [**quanteda** channel on StackOverflow](https://stackoverflow.com/questions/tagged/quanteda).
* See our [tutorial site](https://tutorials.quanteda.io/).
### Cite the package
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](https://www.theoj.org/joss-papers/joss.00774/10.21105.joss.00774.pdf)". _Journal of Open Source Software_. 3(30), 774. [https://doi.org/10.21105/joss.00774](https://doi.org/10.21105/joss.00774).
For a BibTeX entry, use the output from `citation(package = "quanteda")`.
### Leave Feedback
If you like **quanteda**, please consider leaving [feedback or a testimonial here](https://github.com/quanteda/quanteda/issues/461).
### Contribute
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](https://help.github.com/articles/creating-a-pull-request-from-a-fork/) through the [project GitHub page](https://github.com/quanteda/quanteda). See our [Contributor Code of Conduct](https://github.com/quanteda/quanteda/blob/master/CONDUCT.md) and the all-important **quanteda** [Style Guide](https://github.com/quanteda/quanteda/wiki/Style-guide).
* Issues, bug reports, and wish lists: [File a GitHub issue](https://github.com/quanteda/quanteda/issues).
* Contact [the maintainer](mailto:kbenoit@lse.ac.uk) by email.