  In this paper we introduce the concept of multiple bipolar fuzzy measures as
a generalization of a bipolar fuzzy measure. We also propose a new definition
of a group, which is based on the multidimensional bipolar fuzzy relations of
its elements. Taking into account this information, we provide a novel
procedure (based on the well-known Louvain algorithm) to deal with community
detection problems. This new method considers the multidimensional bipolar
information provided by multiple bipolar fuzzy measures, as well as the
information provided by a graph. We also give some detailed computational
tests, obtained from the application of this algorithm in several benchmark
models.
