Zusammenfassung
During the last decade, the science of networks has grown into an enormous
interdisciplinary endeavor, with methods and applications drawn from across the
natural, social, and information sciences. One of the most important and
prominent ideas from network science is the algorithmic detection of
tightly-connected groups of nodes known as communities. Here we develop a
formulation to detect communities in a very broad setting by studying general
dynamical processes on networks. We create a new framework of network quality
functions that allows us to study the community structure of arbitrary
multislice networks, which are combinations of individual networks coupled
through additional links that connect each node in one network slice to itself
in other slices. This new framework allows one for the first time to study
community structure in a very general setting that encompasses networks that
evolve in time, have multiple types of ties (multiplexity), and have multiple
scales.
Nutzer