Mapping nonlocal relationships between metadata and network structure with metadata-dependent encoding of random walks.

ABSTRACT: Integrating structural information and metadata, such as gender, social status, or interests, enriches networks and enables a better understanding of the large-scale structure of complex systems. However, existing approaches to augment networks with metadata for community detection only consider immediately adjacent nodes and cannot exploit the nonlocal relationships between metadata and large-scale network structure present in many spatial and social systems. Here, we develop a flow-based community detection framework based on the map equation that integrates network information and metadata of distant nodes and reveals more complex relationships. We analyze social and spatial networks and find that our methodology can detect functional metadata-informed communities distinct from those de

SUBMITTER: Bassolas A 

PROVIDER: S-EPMC9616498 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature