  The investigation of network structure has important significance to
understand the functions of various complex networks. The communities with
hierarchical and overlapping structures and the special nodes like hubs and
outliers are all common structure features to the networks. Network structure
investigation has attracted considerable research effort recently. However,
existing studies have only partially explored the structure features. In this
paper, a label propagation based integrated network structure investigation
algorithm (LINSIA) is proposed. The main novelty here is that LINSIA can
uncover hierarchical and overlapping communities, as well as hubs and outliers.
Moreover, LINSIA can provide insight into the label propagation mechanism and
propose a parameter-free solution that requires no prior knowledge. In
addition, LINSIA can give out a soft-partitioning result and depict the degree
of overlapping nodes belonging to each relevant community. The proposed
algorithm is validated on various synthetic and real-world networks.
Experimental results demonstrate that the algorithm outperforms several
state-of-the-art methods.
