Identifying and characterizing key nodes among communities based on electrical-circuit networks
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 compl...
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| Veröffentlicht in: | PloS one 2014-06, Vol.9 (6), p.e97021-e97021 |
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| creator | Zhu, Fenghui Wang, Wenxu Di, Zengru Fan, Ying |
| description | 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. |
| doi_str_mv | 10.1371/journal.pone.0097021 |
| format | Article |
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This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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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.</description><subject>Algorithms</subject><subject>Biology and Life Sciences</subject><subject>Communities</subject><subject>Community Networks</subject><subject>Community structure</subject><subject>Computer and Information Sciences</subject><subject>Conservation</subject><subject>Electricity</subject><subject>Engineering and Technology</subject><subject>Humans</subject><subject>Knowledge management</subject><subject>Local flow</subject><subject>Methods</subject><subject>Models, Theoretical</subject><subject>Networks</subject><subject>Neural networks</subject><subject>Nodes</subject><subject>Social networks</subject><subject>Social organization</subject><subject>Social Sciences</subject><subject>Systems 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| subjects | Algorithms Biology and Life Sciences Communities Community Networks Community structure Computer and Information Sciences Conservation Electricity Engineering and Technology Humans Knowledge management Local flow Methods Models, Theoretical Networks Neural networks Nodes Social networks Social organization Social Sciences Systems science |
| title | Identifying and characterizing key nodes among communities based on electrical-circuit networks |
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