Community detection in networks is one of the most popular topics of modern network science. Communities, or clusters, are usually groups of vertices having higher probability of being connected to each other than to members of other groups, though other patterns are possible. Identifying communities is an ill-defined problem. There are no universal protocols on the fundamental ingredients, like the definition of community itself, nor on other crucial issues, like the validation of algorithms and the comparison of their performances. This has generated a number of confusions and misconceptions, which undermine the progress in the field. We offer a guided tour through the main aspects of the problem. We also point out strengths and weaknesses of popular methods, and give directions to their use.
The authors REF ) offer a guided tour of the main aspects of this issue, discuss the strengths and weaknesses of popular methods, and provide guidance on how to use them.
Community detection in networks: A user guide
Physics Reports 659, 1-44 (2016)
Mathematics Physics Computer Science