Nonassortative relationships between groups of nodes are typical in complex networks.

ABSTRACT: Decomposing a graph into groups of nodes that share similar connectivity properties is essential to understand the organization and function of complex networks. Previous works have focused on groups with specific relationships between group members, such as assortative communities or core-periphery structures, developing computational methods to find these mesoscale structures within a network. Here, we go beyond these two traditional cases and introduce a methodology that is able to identify and systematically classify all possible community types in directed multi graphs, based on the pairwise relationship between groups. We apply our approach to 53 different networks and find that assortative communities are the most common structures, but that previously unexplored types appear in alm

SUBMITTER: Liu CX 

PROVIDER: S-EPMC10681970 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature