Cheating in Ranking Systems

Abstract

Consider a software application that pays a commission fee to be sold on an on-line platform (e.g., Google Play). The sales depend on the applications’ customer rankings. Therefore, developers have an incentive to dishonestly promote their application’s ranking, e.g., by faking positive customer reviews. The platform detects dishonest behavior (cheating) with some probability, and then decides whether to ban the application. We provide an analysis and find the equilibrium behaviors of both the application (cheat or not) and the platform (setting the commission fee). We provide insights into how the platform’s detection accuracy affects the incentives of the application’s developers.