This is not the production server. Use unless you explicitly want to use this server. Changes made here will probably not be saved


The Amsterdam Content Analysis Toolkit (AmCAT) is an open source infrastructure that makes it easy to do large-scale automatic and manual content analysis (text analysis) for the social sciences and humanities. Scroll down for more information

AmCAT was originally developed by Wouter van Atteveldt and is currently maintained by him together with Martijn Bastiaan and Christian Stuart. This server is hosted by the VU University Amsterdam and can be used free of charge for small scale projects. AmCAT is completely open source, and you are welcome to to set up your own server. Help improve AmCAT by contributing to the documentation, reporting issues, and contribute to the development!

What is AmCAT?

Document Management

AmCAT is a document management and analysis infrastructure aimed at (e-)humanities and (e-)social science.

Your data

AmCAT makes it easy to upload, analyse, and sample your data. You keep full control over your data, you can share it, keep it closed, and export it when needed.

Powerful analysis

AmCAT makes it easy to access both simple and sophisticated quantitative analyses. AmCAT allows power users to directly access data and processing actions through the REST interface, allowing easy integration with e.g. R analyses.

Why AmCAT?

Open source

AmCAT is fully open source and published on github. This means that you can inspect the code, suggest improvements, and setup your own server as needed. You are never dependent on us for your data or analyses.

Open platform

AmCAT makes your data available using existing open standards and a public API, so you can always get to your data, from your browser or directly from your analysis scripts. By using a flexible plugin structure where, AmCAT makes it easy to add your own analyses.

Open for business

AmCAT has been running for more than 10 years, and is continuously improved. It has been used in various national and international research projects, and is used in teaching quantitative content analysis to hundreds of undergrad students each year.

Curious? Visit the wiki for more information, or just create an account and have a look!