  The information flow inside a P2P network is highly dependent on the network
structure. In order to ease the diffusion of relevant data toward interested
peers, many P2P protocols gather similar nodes by putting them in direct
contact. With this approach the similarity between nodes is computed in a
point-to-point fashion: each peer individually identifies the nodes that share
similar interests with it. This leads to the creation of a sort of "private"
communities, limited to each peer neighbors list. This "private" knowledge do
not allow to identify the features needed to discover and characterize the
correlations that collect similar peers in broader groups. In order to let
these correlations to emerge, the collective knowledge of peers must be
exploited. One common problem to overcome in order to avoid the "private"
vision of the network, is related to how distributively determine the
representation of a community and how nodes may decide to belong to it. We
propose to use a gossip-like approach in order to let peers elect and identify
leaders of interest communities. Once leaders are elected, their profiles are
used as community representatives. Peers decide to adhere to a community or
another by choosing the most similar representative they know about.
