NeurIPS 2020poster21 citations

Content Provider Dynamics and Coordination in Recommendation Ecosystems

Omer Ben-Porat, Itay Rosenberg, Moshe Tennenholtz

Abstract

Recommendation Systems like YouTube are vibrant ecosystems with two types of users: Content consumers (those who watch videos) and content providers (those who create videos). While the computational task of recommending relevant content is largely solved, designing a system that guarantees high social welfare for \textit{all} stakeholders is still in its infancy. In this work, we investigate the dynamics of content creation using a game-theoretic lens. Employing a stylized model that was recently suggested by other works, we show that the dynamics will always converge to a pure Nash Equilibrium (PNE), but the convergence rate can be exponential. We complement the analysis by proposing an efficient PNE computation algorithm via a combinatorial optimization problem that is of independent interest.

BibTeX
@inproceedings{NEURIPS2020_dabd8d2c,
 author = {Ben-Porat, Omer and Rosenberg, Itay and Tennenholtz, Moshe},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
 pages = {18931--18941},
 publisher = {Curran Associates, Inc.},
 title = {Content Provider Dynamics and Coordination in Recommendation Ecosystems},
 url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/dabd8d2ce74e782c65a973ef76fd540b-Paper.pdf},
 volume = {33},
 year = {2020}
}