Informfully

Appearance

Informfully@ RecSys '25

Your All-in-One Solution for User Studies

Contact us
Download Informfully
Informfully LogoInformfully Logo

📊 Real-time monitoring

Look at how your users rate and engage with the recommended content. All interactions can be monitored online and exported.

🎥 Multimedia content

Pictures, podcasts, videos, or a mix of everything! Informfully supports a wide range of content types that you can push to users at any time.

📝 In-app surveys

The app features a built-in survey tool that allows you to send questionnaires to the participants and personalized notifications. Evaluate the answers automatically and export them.

🔬 Use it for your own research

You can use Informfully for free in your own research. It can be custom-tailored to your preferences and experimental design.

Research Platform for Reproducible User Studies ​

Informfully is a research platform for content distribution and user studies. The platform enables the delivery of algorithmically curated text, image, audio, and video content to users and automatically generates a detailed log of their consumption history. It is an open-source platform for conducting user experiments to investigate the impact of item recommendations on users’ consumption behavior. You can get more information here.

Resources ​

Informfully Recommenders

Informfully Recommenders paper our reproducibility framework:

Download Resource Paper

Informfully Recommenders Repo

GitHub Repository for Informfully Recommenders:

GitHub Repository

Online Documentation

Read the online documentation for Informfully Recommenders:

Online Documentation

RecSys '25 Presentation

Download the presentation slides for the Framework:

Download Presentation

D-RDW

D-RDW paper our diversity-driven news recommendations:

Download Short Paper

D-RDW Repo

GitHub Repository for D-RDW experiments:

GitHub Repository

Tutorial Notebook

Check out the tutorial notebook for D-RDW:

View Notebook

RecSys '25 Presentation

Download the presentation slides for the Algorithm:

Download Presentation

NORMalize Workshop Paper

NORMalize paper on our news experiments with recommenders:

Download NORMalize Workshop Paper

Open-Source Dataset

Open-Source Dataset for NORMalize Workshop Paper:

Open-Source Dataset

NORMalize '25 Presentation

Download the presentation slides for NORMalize:

Download Presentation

RecSys '24 Resource Paper

Click here to download our RecSys '24 paper submission on the Informfully platform:

Download RecSys Resource Paper

RecSys '23 Research Paper

Click here to download our RecSys '23 paper submission on 'Deliberative Diversity for News Recommenders':

Download Research Paper

Related Studies

Read our previous journal article on the impact of diversity-optimized recommenders for participatory diversity:

Download Research Paper

We are hiring! ​

Are you interested in large-scale recommender systems and saving society? Then apply to our open position:

Download Now

Informfully is availabe for Android and iOS. The download is free. To get access to the full set of features, you need to be enrolled in a user study. Send an e-mail to to get full access.
App StoreGoogle Play

Community ​

Thank you for your visit to RecSys '25! We are looking forward to your feedback and contributions. Feel free to contact us and join our community.

GitHub Twitter

Made with in Switzerland