Game analysis of user participation in collaborative filtering systems

User participation, i.e. providing ratings to the recommendation server, is of vital importance for the success of collaborative filtering-based recommendation systems. As the name collaborative suggests, whether a user can get high-quality recommendations depends not only on the user himself/herself but also on other users. However, due to the rating cost, rational users prefer to provide as few ratings as possible. In this paper, we model the interactions among users as a game with incomplete information and apply the notion of satisfaction equilibrium (SE) to the proposed game. Every user is assumed to have an expectation for the recommendation quality, and when all users' expectations are satisfied, a SE of the game is achieved. We design a behavior rule which allows users to achieve a SE via iteratively rating items. Theoretical analysis and simulation results demonstrate that, if all users have moderate expectations for recommendation quality and satisfied users are willing to provide more ratings, then all users can get satisfying recommendations without providing many ratings. We hope the game analysis presented in this paper can provide some implications for designing mechanisms to encourage user participation.