scholarly journals Time‐varying nodal measures with temporal community structure: A cautionary note to avoid misinterpretation

2020 ◽  
Vol 41 (9) ◽  
pp. 2347-2356 ◽  
Author(s):  
William Hedley Thompson ◽  
Granit Kastrati ◽  
Karolina Finc ◽  
Jessey Wright ◽  
James M. Shine ◽  
...  
Keyword(s):  
Community Structure ◽  
Time Varying ◽  
Cautionary Note

scholarly journals Time-varying nodal measures with temporal community structure: a cautionary note to avoid misinterpretation

2019 ◽  
Author(s):  
WH Thompson ◽  
G Kastrati ◽  
K Finc ◽  
J Wright ◽  
JM Shine ◽  
...  
Keyword(s):  
Community Structure ◽  
Network Models ◽  
Time Varying ◽  
Temporal Network ◽  
Cautionary Note ◽  
Network Properties ◽  
Nodal Properties ◽  
Network Neuroscience

AbstractIn network neuroscience, temporal network models have gained popularity. In these models, network properties have been related to cognition and behaviour. Here we demonstrate that calculating nodal properties that are dependent on temporal community structure (such as the participation coefficient) in time-varying contexts can potentially lead to misleading results. Specifically, with regards to the participation coefficient, increases in integration can be inferred when the opposite is occuring. Further, we present a temporal extension to the participation coefficient measure (temporal participation coefficient) that circumnavigates this problem by jointly considering all community partitions assigned to a node through time. The proposed method allows us to track a node’s integration through time while adjusting for the possible changes in the community structure of the overall network.

scholarly journals Common community structure in time-varying networks

2012 ◽  
Vol 85 (5) ◽  
Author(s):  
Shihua Zhang ◽  
Junfei Zhao ◽  
Xiang-Sun Zhang
Keyword(s):  
Community Structure ◽  
Time Varying ◽  
Time Varying Networks

scholarly journals An Efficient Hierarchy Algorithm for Community Detection in Complex Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Lili Zhang ◽  
Qing Ye ◽  
Yehong Shao ◽  
Chenming Li ◽  
Hongmin Gao
Keyword(s):  
Graph Theory ◽  
Community Structure ◽  
Complex Networks ◽  
Community Detection ◽  
High Accuracy ◽  
Time Varying ◽  
Local Connectedness ◽  
Fine Grained ◽  
Cn Algorithm ◽  
Agglomerative Algorithm

Community structure is one of the most fundamental and important topology characteristics of complex networks. The research on community structure has wide applications and is very important for analyzing the topology structure, understanding the functions, finding the hidden properties, and forecasting the time-varying of the networks. This paper analyzes some related algorithms and proposes a new algorithm—CN agglomerative algorithm based on graph theory and the local connectedness of network to find communities in network. We show this algorithm is distributed and polynomial; meanwhile the simulations show it is accurate and fine-grained. Furthermore, we modify this algorithm to get one modified CN algorithm and apply it to dynamic complex networks, and the simulations also verify that the modified CN algorithm has high accuracy too.

Cluster Mixed Synchronization of Complex Networks with Disturbance

2015 ◽  
Vol 719-720 ◽  
pp. 448-451
Author(s):  
Li Jie Zeng
Keyword(s):  
Community Structure ◽  
Complex Networks ◽  
Numerical Simulations ◽  
Network Model ◽  
Complex Dynamical Networks ◽  
Time Varying ◽  
Dynamical Networks ◽  
Bounded Disturbances ◽  
Synchronization Scheme ◽  
Theoretical Results

In this paper, we investigate the cluster mixed synchronization scheme in time-varying delays coupled complex dynamical networks with disturbance. Basing on the community structure of the networks, some sufficient criteria are derived to ensure cluster mixed synchronization of the network model. Particularly, unknown bounded disturbances can be conquered by the proposed control. The numerical simulations are performed to verify the effectiveness of the theoretical results

scholarly journals Cluster Anti-Synchronization of Complex Networks with Nonidentical Dynamical Nodes

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Shuguo Wang ◽  
Chunyuan He ◽  
Hongxing Yao
Keyword(s):  
Community Structure ◽  
Complex Networks ◽  
Numerical Simulations ◽  
Network Model ◽  
Complex Dynamical Networks ◽  
Time Varying ◽  
Dynamical Networks ◽  
Nonidentical Nodes ◽  
Theoretical Results

This paper investigates a new cluster antisynchronization scheme in the time-varying delays coupled complex dynamical networks with nonidentical nodes. Based on the community structure of the networks, the controllers are designed differently between the nodes in one community that have direct connections to the nodes in other communities and the nodes without direct connections with the nodes in other communities strategy; some sufficient criteria are derived to ensure cluster anti-synchronization of the network model. Particularly, the weight configuration matrix is not assumed to be irreducible. The numerical simulations are performed to verify the effectiveness of the theoretical results.

scholarly journals Cluster Synchronization of Time-Varying Delays Coupled Complex Networks with Nonidentical Dynamical Nodes

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Shuguo Wang ◽  
Hongxing Yao ◽  
Mingping Sun
Keyword(s):  
Community Structure ◽  
Complex Networks ◽  
Numerical Simulations ◽  
Network Model ◽  
Complex Dynamical Networks ◽  
Cluster Synchronization ◽  
Time Varying ◽  
Dynamical Networks ◽  
Synchronization Scheme ◽  
Theoretical Results

This paper investigates a new cluster synchronization scheme in the nonlinear coupled complex dynamical networks with nonidentical nodes. The controllers are designed based on the community structure of the networks; some sufficient criteria are derived to ensure cluster synchronization of the network model. Particularly, the weight configuration matrix is not assumed to be symmetric, irreducible. The numerical simulations are performed to verify the effectiveness of the theoretical results.

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