Do you want to push news, videos, songs, or pictures to user panels and see how they react? We got you covered! Informfully is an all-in-one content delivery platform that allows you to set up your user studies within minutes. No coding required! Run it on Android, iOS, or in your browser. Give it a try and download it right now!
Informfully is fully open-source. Become a member today!
Thank you for choosing Informfully! Access the code on GitHub and become part of our community. We’d love to hear your feedback and welcome any contributions. Don’t hesitate to reach out at info@informfully.ch.
Made with in Switzerland
Reach out to use via info@informfully.ch to get access to the app's website for setting up your own user study. It is completely free!
We provide you a web interface to configure your user study and to open accounts for your users. They can be exported and redistributed outside of our platform.
Send us your multimedia items that you want to push to the users. Are you not allowed to share the content? You can also just give us a pointer to the online resource via an API. We take care of the rest.
Specify for each user what, how, and when they should see a specific piece of content. Select from among the built-in solutions or run your own model and forward us the results.
Create complementary questionnaires to gather feedback. You can attach specific feedback questions or rating options for each recommendation.
You can launch betas to test everything. Once you are ready, launch the experiment. All interactions are stored and you can download the data at any point.
As part of Informfully's commitment to research, the services are offered free of charge to research institutions. Take a look at the projects below to see how Informfully was successfully used in the past to support research.
User study on the impact of deliberative diversity that over-exposes minority voices in political discussions.
available onlineField experiment on topic diversity and how it impact user's perception of news and engagement rates.
available onlineIf you use any Informfully code/repository in a scientific publication, we ask you to cite the following papers:
@inproceedings{heitz2024informfully,
title={Informfully - Research Platform for Reproducible User Studies},
author={Heitz, Lucien and Croci, Julian A and Sachdeva, Madhav and Bernstein, Abraham},
booktitle={Proceedings of the 18th ACM Conference on Recommender Systems},
year={2024}
}@inproceedings{heitz2023deliberative,
title={Deliberative Diversity for News Recommendations: Operationalization and Experimental User Study},
author={Heitz, Lucien and Lischka, Juliane A and Abdullah, Rana and Laugwitz, Laura and Meyer, Hendrik and Bernstein, Abraham},
booktitle={Proceedings of the 17th ACM Conference on Recommender Systems},
pages={813--819},
year={2023}
}@article{heitz2022benefits,
title={Benefits of diverse news recommendations for democracy: A user study},
author={Heitz, Lucien and Lischka, Juliane A and Birrer, Alena and Paudel, Bibek and Tolmeijer, Suzanne and Laugwitz, Laura and Bernstein, Abraham},
journal={Digital Journalism},
volume={10},
number={10},
pages={1710--1730},
year={2022},
publisher={Taylor \& Francis}
}You are welcome to contribute to the Informfully ecosystem and become a part of our community. Feel free to:
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.)