Informfully @
RecSys '25
Informfully is a research platform for content distribution and user studies. The platform allows to push 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.
Informfully Recommenders paper our reproducibility framework:
D-RDW paper our diversity-driven news recommendations:
NORMalize paper on our news experiments with recommenders:
Are you interested in large-scale recommender systems and saving society? Then apply to our open position:
Click here to download our RecSys '24 paper submission on the Informfully platform:
Click here to download our RecSys '23 paper submission on 'Deliberative Diversity for News Recommenders':
Read our previous journal article on the impact of diviersity-optimized recommenders for participatory diversity:
