A network-based rating system and its resistance to bribery

Abstract

We study a rating system in which a set of individ- uals (e.g., the customers of a restaurant) evaluate a given service (e.g, the restaurant), with their ag- gregated opinion determining the probability of all individuals to use the service and thus its generated revenue. We explicitly model the influence relation by a social network, with individuals being influ- enced by the evaluation of their trusted peers. On top of that we allow a malicious service provider (e.g., the restaurant owner) to bribe some individ- uals, i.e., to invest a part of his or her expected in- come to modify their opinion, therefore influenc- ing his or her final gain. We analyse the effect of bribing strategies under various constraints, and we show under what conditions the system is bribery- proof, i.e., no bribing strategy yields a strictly pos- itive expected gain to the service provider