Bribery in Rating System: A Game-Theoretic Perspective.
Year: 2019
Type: preprint
Abstract: 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 concentrates on the analysis of the static game with a fixed number of sellers and buyers, then we model a real-world setting towards a dynamic game. On top of our analysis, we conclude that at least one Nash equilibrium can be reached in the bribery game of the rating system.
Source: arXiv (Cornell University)
Language: English
Topic: Game Theory and Applications
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2989982143