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Trust and reputation measures are crucial in distributed open systems where agents need to decide whom or what to choose. Existing work has overlooked the impact of an entity's position in its structural graph and its effect on the propagation of trust in such graphs. This paper presents an algorithm for the propagation of reputation in structural graphs. It allows agents to infer their opinion about unfamiliar entities based on their view of related entities. The proposed mechanism focuses on the “part of” relation to illustrate how reputation may flow (or propagate) from one entity to another. The paper bases its reputation measures on opinions, which it defines as probability distributions over an evaluation space, providing a rich representation of opinions.