quanteda

quanteda: An R package for the quantitative analysis of textual data - Published in JOSS (2018)

https://github.com/quanteda/quanteda

Keywords

Keywords from Contributors

Repository

An R package for the Quantitative Analysis of Textual Data

README.Rmd

---
output: github_document
---

```{r, echo = FALSE}
knitr::opts_chunk$set(
 warning = FALSE,
 collapse = TRUE,
 comment = "##",
 fig.path = "man/images/"
)
```
```{r echo=FALSE, results="hide", message=FALSE}
library("badger")
```

[![quanteda: quantitative analysis of textual data](https://cdn.rawgit.com/quanteda/quanteda/master/images/quanteda_logo.svg)](http://quanteda.io)


[![CRAN Version](https://www.r-pkg.org/badges/version/quanteda)](https://CRAN.R-project.org/package=quanteda)
`r badge_devel("quanteda/quanteda", "royalblue")`
[![Downloads](https://cranlogs.r-pkg.org/badges/quanteda)](https://CRAN.R-project.org/package=quanteda)
[![Total Downloads](https://cranlogs.r-pkg.org/badges/grand-total/quanteda?color=orange)](https://CRAN.R-project.org/package=quanteda)
[![R-CMD-check](https://github.com/quanteda/quanteda/actions/workflows/check-standard.yaml/badge.svg)](https://github.com/quanteda/quanteda/actions/workflows/check-standard.yaml)
[![codecov](https://codecov.io/gh/quanteda/quanteda/branch/master/graph/badge.svg)](https://app.codecov.io/gh/quanteda/quanteda) [![DOI](https://zenodo.org/badge/5424649.svg)](https://zenodo.org/badge/latestdoi/5424649)
[![DOI](http://joss.theoj.org/papers/10.21105/joss.00774/status.svg)](https://doi.org/10.21105/joss.00774)


## About


**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).

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

## **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 make the default tokeniser smarter than ever, with new Unicode and ICU-compliant rules enabling 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**](https://github.com/quanteda/quanteda): contains all of the core natural language processing and textual data management functions
- [**quanteda.textmodels**](https://github.com/quanteda/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**](https://github.com/quanteda/quanteda.textstats): statistics for textual data, namely the `textstat_*()` functions, split with the v3 release
- [**quanteda.textplots**](https://github.com/quanteda/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**](https://github.com/quanteda/quanteda.sentiment): Functions and lexicons for sentiment analysis using dictionaries
- [**quanteda.tidy**](https://github.com/quanteda/quanteda.tidy): Extensions for manipulating document variables in core **quanteda** objects using your favourite **tidyverse** functions

and more to come.

## 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
```

### 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.



### Enable parallelisation


**quanteda** takes advantage of parallel computing through the [TBB (Threading Building Blocks) library](https://en.wikipedia.org/wiki/Threading_Building_Blocks) to speed up computations. This guide provides step-by-step instructions on how to set up your system for using Quanteda with parallel capabilities on Windows, macOS, and Linux.


**Windows:**

Download and install RTools from [RTools download page](https://cran.r-project.org/bin/windows/Rtools/).


**macOS:**

1. **Install XCode Command Line Tools**
   - Type the following command in the terminal:
     ```bash
     xcode-select --install
     ```
     
2. **Install Homebrew**
   - If Homebrew is not installed, run:
     ```bash
     /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
     ```

3. **Install TBB and pkg-config**
   - After installing Homebrew, run:
     ```bash
     brew install tbb pkg-config
     ```

4. **Install gfortran**
   - Required for compiling Fortran code, install using Homebrew:
     ```bash
     brew install gcc
     ```

**Linux:**

Install TBB:

- For Fedora, CentOS, RHEL:
  ```bash
  sudo yum install tbb-devel
  ```
- For Debian and Ubuntu:
  ```bash
  sudo apt install libtbb-dev
  ```

More details are provided in the [quanteda documentation](http://quanteda.io/articles/pkgdown/parallelisation.html).


### 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.
* Check out the [**quanteda** cheatsheet](https://github.com/quanteda/quanteda/blob/master/tests/cheatsheet/quanteda-cheatsheet.pdf).
* Submit a question on the **quanteda** channel on StackOverflow (questions tagged as 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.

Owner

JOSS Publication

quanteda: An R package for the quantitative analysis of textual data

Published

October 06, 2018

DOI

10.21105/joss.00774

Volume 3, Issue 30, Page 774

Authors

Kenneth Benoit
Department of Methodology, London School of Economics and Political Science

Kohei Watanabe
Department of Methodology, London School of Economics and Political Science

Haiyan Wang
De Beers Inc.

Paul Nulty
Centre for Research in Arts, Social Science and Humanities, University of Cambridge

Adam Obeng
Facebook, Inc. (work conducted at the Department of Methodology, London School of Economics and Political Science)

Stefan Müller
Department of Political Science, Trinity College Dublin

Akitaka Matsuo
Department of Methodology, London School of Economics and Political Science

Editor

Arfon Smith

Tags

text mining natural language processing

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