Bribery in Rating System: A Game-Theoretic Perspective

The rich revenue gained from a mobile application ($a.k.a.$ app) boost app owners (sellers) to manipulate the app store with fake ratings. One effective way to hire fake rating providers is bribery. The fake ratings given by the bribed buyers influence the evaluation of the app, which further have an impact on the decision-making of potential buyers. In this paper, we study bribery in a rating system with multiple sellers and buyers, which extends the single seller situation discussed in \cite{Grandi2016}. We analyze the effect of bribing strategy using game theory methodology and examine the existence of its an equilibrium state, in which the rating system is expected to be bribery-proof: no bribery strategy yields a strictly positive expected gain to the seller. Our study first concentrate on the analysis of static game with a fixed number of sellers and buyers, then we model real-world setting towards a dynamic game. On top of our analysis, we conclude at least one Nash equilibrium can be reached in the bribery game of rating system.