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