index.Rmd

---
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 textual data developed by [Kenneth Benoit](http://kenbenoit.net) 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.

## How to Install

The normal way from CRAN, using your R GUI or 
```{r eval = FALSE}
install.packages("quanteda") 
```

Or for the latest development version:
```{r eval = FALSE}
# devtools package required to install quanteda from Github 
devtools::install_github("quanteda/quanteda") 
```

Because this compiles some C++ and Fortran source code, you will need to have installed the appropriate compilers.

**If you are using a Windows platform**, this means you will need also to install
the [Rtools](https://CRAN.R-project.org/bin/windows/Rtools/) software available
from CRAN.  

**If you are using macOS**, you should install the 
[macOS tools](https://cran.r-project.org/bin/macosx/tools/), 
namely the Clang 6.x compiler and the GNU Fortran compiler (as **quanteda** requires gfortran to build).
 If you are still getting errors related to gfortran, follow the fixes [here](https://thecoatlessprofessor.com/programming/rcpp-rcpparmadillo-and-os-x-mavericks--lgfortran-and--lquadmath-error/).  
 
## System Requirements

**quanteda** is cross-platform but we recommend MacOS or Linux as an operating system for their better handling of Unicode. RAM depends on the size and the structure of the textual data to analyse. Usually, a text file of 100MB on disk takes 500MB to 1GB on memory as a tokens object (short texts require more memory than long texts when the total numbers of words are the same). 

| | Minimum | Recommended |
| --- | :---: | :---: |
| OS | Windows/MacOS/Linux | MacOS/Linux |
| CPU | 1 core | 4 cores or more |
| RAM | 2GB | 8GB more more |
| IDE | | R Studio |    

## How to Use 

See the [quick start guide](https://quanteda.io/articles/quickstart.html) to learn how to use **quanteda**.

## How to cite

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")`.

## Leaving Feedback

If you like **quanteda**, please consider leaving [feedback or a testimonial here](https://github.com/quanteda/quanteda/issues/461).

## Contributing

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).
*  Usage questions:  Submit a question on the [**quanteda** channel on StackOverflow](https://stackoverflow.com/questions/tagged/quanteda).
*  Contact [the maintainer](mailto:kbenoit@lse.ac.uk) by email.