  In the Internet era the information overload and the challenge to detect
quality content has raised the issue of how to rank both resources and users in
online communities. In this paper we develop a general ranking method that can
simultaneously evaluate users' reputation and objects' quality in an iterative
procedure, and that exploits the trust relationships and social acquaintances
of users as an additional source of information. We test our method on two real
online communities, the EconoPhysics forum and the Last.fm music catalogue, and
determine how different variants of the algorithm influence the resultant
ranking. We show the benefits of considering trust relationships, and define
the form of the algorithm better apt to common situations.
