Welcome to Informfully (GitHub & Website)! Informfully is an open-source reproducibility platform for content distribution and user experiments.
Links and Resources: GitHub | Website | X | Documentation | DDIS@UZH | Google Play | App Store
This repository contains all the experiment scripts (configuration files and hyperparameters) to reproduce the findings of our papers and research that use the Informfully Recommenders. For an overview of how to run the experiment workflows shared here, please go through the tutorial below. The tutorial includes step-by-step instructions for downloading the codebase necessary to run all the models and scripts listed here.
| Experiment | Resources |
|---|---|
| Benefits of Diverse News Recommendations for Democracy (DJ '22) | Paper, Model |
| Deliberative Diversity for News Recommendations (RecSys '23) | Paper, Model, Scripts |
| Random Walks for Diverse News Recommendations (RecSys '24) | Paper, Model, Scripts |
| Position and Accessibility Nudges for News (JOC '25, NORMalize '24) | Paper 1, Paper 2, Scripts, Dataset |
| Diversity-Driven Random Walks (RecSys '25) | Paper, Model, Scripts |
| Informfully Recommenders (RecSys '25) | Paper, Scripts |
Please see the Informfully Recommenders Tutorial for instructions on how to work with our scripts and recommendation pipelines. To get started, you first need to download the codebase we share in the repository of the Recommender Framework.
You are welcome to contribute to the Informfully ecosystem and become a part of our community. Feel free to:
- Fork any of the Informfully repositories.
- Suggest new features in Future Release.
- Make changes and create pull requests.
Please post your feature requests and bug reports in our GitHub issues section.
Released under the MIT License. (Please note that the respective copyright licenses of third-party libraries and dependencies apply.)
