Relational flexibility of network elements based on inconsistent community detection

Abstract

Community identification of network components enables us to understand the mesoscale clustering structure of networks. A number of algorithms have been developed to determine the most likely community structures in networks. Such a probabilistic or stochastic nature of this problem can naturally involve the ambiguity in resultant community structures. More specifically, stochastic algorithms can result in different community structures for each realization in principle. In this study, instead of trying to "solve" this community degeneracy problem, we turn the tables by taking the degeneracy as a chance to quantify how strong companionship each node has with other nodes. For that purpose, we define the concept of companionship inconsistency that indicates how inconsistently a node is identified as a member of a community regarding the other nodes. Analyzing model and real networks, we show that companionship inconsistency discloses unique characteristics of nodes, thus we suggest it as a new type of node centrality. In social networks, for example, companionship inconsistency can classify outsider nodes without firm community membership and promiscuous nodes with multiple connections to several communities. In infrastructure networks such as power grids, it can diagnose how the connection structure is evenly balanced in terms of power transmission. Companionship inconsistency, therefore, abstracts individual nodes' intrinsic property on its relationship to a higher-order organization of the network.

10 pages, 5 figures, 2 tables

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Cited by in corpus (13)

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• Power-grid stability predictions using transferable machine learning
• Consistency landscape of network communities
• On structural and dynamical factors determining the integrated basin instability of power-grid nodes
• Multi-scale Laplacian community detection in heterogeneous networks
• Identifying robust features of community structure in complex networks
• TempoCave: Visualizing Dynamic Connectome Datasets to Support Cognitive Behavioral Therapy
• How modular structure determines operational resilience of power grids
• Exploring 3D community inconsistency in human chromosome contact networks
• Refinement for community structures of bipartite networks
• Mesoscale properties of mutualistic networks in ecosystems
• Global decomposition of networks into multiple cores formed by local hubs
• Community membership consistency applied to corporate board interlock networks