The semantic fluency task is frequently used in psychology by both reseachers and clinicians. SNAFU is tool that helps you analyze fluency data. It can help with:
- Counting cluster switches and cluster sizes
- Counting perseverations
- Detecting intrusions
- Calculating average age-of-acquisition and word frequency
- ...more!
SNAFU also implements multiple network estimation methods which allow you to perform network analysis on your data (see Zemla & Austerweil, 2018). These methods are implemented:
- U-INVITE networks
- Pathfinder networks
- Correlation-based networks
- Naive random walk network
- Conceptual networks
- First Edge networks
SNAFU can be used as a Python library or as a stand-alone GUI. ThePython library is available here:
https://github.com/AusterweilLab/snafu-py
Or install directly using git (auxilliary files are not included):
pip install git+https://github.com/AusterweilLab/snafu-py
The Github repository contains several demo files, and a full tutorial is in press (pre-print).
A graphical front-end is also available, though it does not contain as many features as the Python library. You can download it for macOS or Windows. Find it here:
| Mac | ||
|---|---|---|
| SNAFU 2.4.1 for macOS (latest version) | ||
| Windows | ||
| SNAFU 2.2.0 for Windows | ||
Check out our Google Group that will be used for troubleshooting. If you have question or comment, e-mail the list at snafu-fluency [at] googlegroups [dot] com