  Community structure exists in many real-world networks and has been reported
being related to several functional properties of the networks. The
conventional approach was partitioning nodes into communities, while some
recent studies start partitioning links instead of nodes to find overlapping
communities of nodes efficiently. We extended the map equation method, which
was originally developed for node communities, to find link communities in
networks. This method is tested on various kinds of networks and compared with
the metadata of the networks, and the results show that our method can identify
the overlapping role of nodes effectively. The advantage of this method is that
the node community scheme and link community scheme can be compared
quantitatively by measuring the unknown information left in the networks
besides the community structure. It can be used to decide quantitatively
whether or not the link community scheme should be used instead of the node
community scheme. Furthermore, this method can be easily extended to the
directed and weighted networks since it is based on the random walk.

Physics and Society;Statistical Mechanics;Social and Information Networks