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


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.
Click here to download our RecSys '24 paper submission on the Informfully platform:
Download RecSys Resource PaperClick here to download our RecSys '24 challenge paper submission on diversity in news recommendations:
Download RecSys Challenge PaperDownload the NORMalize paper on our Informfully dataset IDEA:
Download NORMalize Workshop PaperClick here to download our RecSys '23 paper submission on 'Deliberative Diversity for News Recommenders':
Download Research PaperRead our previous journal article on the impact of diversity-optimized recommenders for participatory diversity:
Download Research PaperInformfully is part of a research endeavor of investigating the normative aspects of news recommendations. Click here to download community manifesto:
Download Research ManifestoWe take part in the discussion of the impact of algorithmic content curation and AI at the OSCE level. Click here to get the most recent policy manual:
Download OSCE BookAre you interested in large-scale recommender systems and their potential to benefit society? Then apply to our open position: