  A new method for identifying communities in networks is proposed. Reference
nodes, either selected using a priory information about the network or
according to relevant node measurements, are obtained so as to indicate
putative communities. Distance vectors between each network node and the
reference nodes are then used for defining a coordinate system representing the
community structure of the network at many different scales. For modular
networks, the distribution of nodes in this space often results in a
well-separated clustered structure, with each cluster corresponding to a
community. One interesting feature of the reported methodology for community
finding is that the coordinate system defined by the seeds allows an intuitive
and direct interpretation of the situation of each node with respect to the
considered communities. The potential of the method is illustrated with respect
to a community detection benchmark, a spatial network model and to city streets
networks.
