title: Identifying and characterizing key nodes among communities based on electrical-circuit networks.
abstract: Complex networks with community structures are ubiquitous in the real world. Despite many approaches developed for detecting communities, we continue to lack tools for identifying overlapping and bridging nodes that play crucial roles in the interactions and communications among communities in complex networks. Here we develop an algorithm based on the local flow conservation to effectively and efficiently identify and distinguish the two types of nodes. Our method is applicable in both undirected and directed networks without a priori knowledge of the community structure. Our method bypasses the extremely challenging problem of partitioning communities in the presence of overlapping nodes that may belong to multiple communities. Due to the fact that overlapping and bridging nodes are of paramount importance in maintaining the function of many social and biological networks, our tools open new avenues towards understanding and controlling real complex networks with communities accompanied with the key nodes.
authors.affiliation: School of Systems Science, Beijing Normal University, Beijing, China.
authors.forename: Fenghui
authors.initials: F
authors.lastname: Zhu
authors.affiliation: School of Systems Science, Beijing Normal University, Beijing, China.
authors.forename: Wenxu
authors.initials: W
authors.lastname: Wang
authors.affiliation: School of Systems Science, Beijing Normal University, Beijing, China.
authors.forename: Zengru
authors.initials: Z
authors.lastname: Di
authors.affiliation: School of Systems Science, Beijing Normal University, Beijing, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Fan
mesh_terms: D000465:Algorithms; D019058:Community Networks; D004560:Electricity; D006801:Humans; D008962:Models, Theoretical