Using mapping entropy to identify node centrality in complex networks

2016 ◽  
Vol 453 ◽  
pp. 290-297 ◽  
Author(s):  
Tingyuan Nie ◽  
Zheng Guo ◽  
Kun Zhao ◽  
Zhe-Ming Lu
Keyword(s):  
Complex Networks ◽  
Node Centrality

Temporal node centrality in complex networks

2012 ◽  
Vol 85 (2) ◽  
Author(s):  
Hyoungshick Kim ◽  
Ross Anderson
Keyword(s):  
Complex Networks ◽  
Node Centrality

scholarly journals Analysis of the effect of node centrality on diffusion mode in complex networks

2017 ◽  
Vol 66 (12) ◽  
pp. 120201
Author(s):  
Su Zhen ◽  
Gao Chao ◽  
Li Xiang-Hua
Keyword(s):  
Complex Networks ◽  
Diffusion Mode ◽  
Node Centrality

scholarly journals TIME CENTRALITY IN DYNAMIC COMPLEX NETWORKS

2015 ◽  
Vol 18 (07n08) ◽  
pp. 1550023 ◽  
Author(s):  
EDUARDO C. COSTA ◽  
ALEX B. VIEIRA ◽  
KLAUS WEHMUTH ◽  
ARTUR ZIVIANI ◽  
ANA PAULA COUTO DA SILVA
Keyword(s):  
Diffusion Process ◽  
Complex Networks ◽  
Diffusion Processes ◽  
Temporal Evolution ◽  
Dynamic Network ◽  
Time Varying ◽  
Relative Importance ◽  
Node Centrality ◽  
Centrality Metrics ◽  
Efficient Diffusion

There is an ever-increasing interest in investigating dynamics in time-varying graphs (TVGs). Nevertheless, so far, the notion of centrality in TVG scenarios usually refers to metrics that assess the relative importance of nodes along the temporal evolution of the dynamic complex network. For some TVG scenarios, however, more important than identifying the central nodes under a given node centrality definition is identifying the key time instants for taking certain actions. In this paper, we thus introduce and investigate the notion of time centrality in TVGs. Analogously to node centrality, time centrality evaluates the relative importance of time instants in dynamic complex networks. In this context, we present two time centrality metrics related to diffusion processes. We evaluate the two defined metrics using both a real-world dataset representing an in-person contact dynamic network and a synthetically generated randomized TVG. We validate the concept of time centrality showing that diffusion starting at the best ranked time instants (i.e., the most central ones), according to our metrics, can perform a faster and more efficient diffusion process.

Complex Networks

2009 ◽  
Author(s):  
Reuven Cohen ◽  
Shlomo Havlin
Keyword(s):  
Complex Networks

Complex Networks from Simple Rules

2013 ◽  
Vol 22 (2) ◽  
pp. 151-174 ◽  
Author(s):  
Richard Southwell ◽  
Jianwei Huang ◽  
Chris Cannings ◽  
◽  
Keyword(s):  
Complex Networks ◽  
Simple Rules
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