4CAT is a research tool that can be used to analyse and process data from online social platforms. Its goal is to make the capture and analysis of data from these platforms accessible to people through a web interface, without requiring any programming or web scraping skills. Our target audience is researchers, students and journalists interested using Digital Methods in their work.
In 4CAT, you create a dataset from a given platform according to a given set of parameters; the result of this (usually a CSV file containing matching items) can then be downloaded or analysed further with a suite of analytical 'processors', which range from simple frequency charts to more advanced analyses such as the generation and visualisation of word embedding models.
4CAT has a (growing) number of supported data sources corresponding to popular platforms that are part of the tool, but you can also add additional data sources using 4CAT's Python API. The following data sources are currently supported actively:
- 4chan
- 8kun
- Bitchute
- Parler
- Telegram
- Twitter API (Academic and regular tracks)
The following platforms are supported through other tools, from which you can import data into 4CAT for analysis:
- Facebook (via CrowdTangle exports)
- Instagram (via CrowdTangle)
- TikTok (via Zeeschuimer or tiktok-scraper)
A number of other platforms have built-in support that is untested, or requires e.g. special API access. You can view the full list of data sources in the GitHub repository.
You can install 4CAT locally or on a server via Docker or manually. The usual
docker-compose up
will work, but detailed and alternative installation instructions are available in our wiki. Currently 4chan, 8chan, and 8kun require additional steps; please see the wiki.
Please check our issues and create one if you experience any problems (pull requests are also very welcome).
4CAT consists of several components, each in a separate folder:
backend: A standalone daemon that collects and processes data, as queued via the tool's web interface or API.webtool: A Flask app that provides a web front-end to search and analyze the stored data with.common: Assets and libraries.datasources: Data source definitions. This is a set of configuration options, database definitions and python scripts to process this data with. If you want to set up your own data sources, refer to the wiki.processors: A collection of data processing scripts that can plug into 4CAT to manipulate or process datasets created with 4CAT. There is an API you can use to make your own processors.
4CAT was created at OILab and the Digital Methods Initiative at the University of Amsterdam. The tool was inspired by DMI-TCAT, a tool with comparable functionality that can be used to scrape and analyse Twitter data.
4CAT development is supported by the Dutch PDI-SSH foundation through the CAT4SMR project.
4CAT is licensed under the Mozilla Public License, 2.0. Refer to the LICENSE
file for more information.