  This study relates the local property of node dominance to local and global
properties of a network. Iterative removal of dominated nodes yields a
distributed algorithm for computing a core-periphery decomposition of a social
network, where nodes in the network core are seen to be essential in terms of
network flow and global structure. Additionally, the connected components in
the periphery give information about the community structure of the network,
aiding in community detection. A number of explicit results are derived,
relating the core and periphery to network flow, community structure and global
network structure, which are corroborated by observational results. The method
is illustrated using a real world network (DBLP co-authorship network), with
ground-truth communities.
