Abstract:
In this paper we introduce a methodology to identify
communities in dark multilayered networks, taking into account
that the main challenges of these networks are incompleteness,
fuzzy boundaries, and dynamic behavior. To account for these
characteristics, we create knowledge sharing communities (KSC)
that determine the community detection. KSC is driven by
weighing the edge attributes as desired for the application that the
communities are used. We provide an interactive algorithm that
allows the operator to decide on the weights and the thresholds
applied to create the communities. By choosing these variables,
our results quantitatively outperform community detection on
the collapsed monoplex network.
