This website contains a step-by-step introduction to quantitative text analysis using quanteda. The chapters cover a brief introduction to the statistical programming language R, how to import text data, basic operations of quanteda, how to construct a corpus, tokens objects, a document-feature matrix, and how to conduct advanced operations. The final chapter deals with text scaling (e.g., Wordscores, Wordfish, correspondence analysis) and document classification using Naive Bayes and topic models.
This website consist of over 30 sections. If you click on the name of a chapter on the left-hand side of this page, the sections will pop up. You can also use the “Search” field in the top-left corner to look up the occurrence of specific terms or R functions covered in the tutorials.
This website is created for workshops held by the quanteda team and for users who look for a comprehensible step-by-step introduction to text analysis using R. We have also created several additional useful resources, such as vignettes, replications, a cheatsheet and a comparison to functions in quanteda and other packages for quantitative text analysis.
Examples in this tutorial are written for quanteda version 3.2.5. Please check if you have the same version installed by a command
You can not only see the R commands but execute them yourself if you download the source code of this website from the Github repository. You should unzip the files on your machine and click
quanteda.tutorials.Rproj to open RStudio. Executable R commands are in the
.Rmarkdown files under the
Contributions in the form of feedback, comments, code, and bug reports are most welcome. If you want to change the content of the pages, please edit the
.Rmarkdown (instead of
.markdown) files in the
content folder and issue a pull request on Github.
If you have questions on how to use quanteda, please post them to the quanteda channel on StackOverflow. If you find a bug, please report it to the quanteda issues. We prefer these platforms to emails in communicating with our users because the records will help other users who face similar problems.
The quanteda package infrastructure and Quanteda Tutorials are collaborative efforts. Many people have contributed fixes and improvements via pull request: Rohan Alexander (@RohanAlexander), Rich Allen (@enzedonline), Andreas Beger (@andybega), Sarah King (@sarahashleyking), Oul Han (@klarahan), Frederik Hjorth (@fghjorth), Sarah Jewett (@SarahJewett), Amit Kohli (@DataStrategist), Lanabi la Lova (@Lanabi), Mohamed Nasr (@mohamednasr1), Alexander Poon (@alexander-poon), Brian Roepke (@broepke), Rochelle Terman (@rochelleterman), Daniela Ushizima (@dani-lbnl), Yuan Zhou (@yuanzhouIR), @datapumpernickel, @fgeeri, @cdedatos.