Node importance for dynamical process on networks: a multiscale characterization.

Defining the importance of nodes in a complex network has been a fundamental problem in analyzing the structural organization of a network, as well as the dynamical processes on it. Traditionally, the measures of node importance usually depend either on the local neighborhood or global properties of a network. Many real-world networks, however, demonstrate finely detailed structure at various organization levels, such as hierarchy and modularity. In this paper, we propose a multiscale node-importance measure that can characterize the importance of the nodes at varying topological scale. This is achieved by introducing a kernel function whose bandwidth dictates the ranges of interaction, and meanwhile, by taking into account the interactions from all the paths a node is involved. We demonstrate that the scale here is closely related to the physical parameters of the dynamical processes on networks, and that our node-importance measure can characterize more precisely the node influence under different physical parameters of the dynamical process. We use epidemic spreading on networks as an example to show that our multiscale node-importance measure is more effective than other measures.

[1]  J. Rogers Chaos , 1876, Molecular Vibrations.

[2]  P. Bonacich Factoring and weighting approaches to status scores and clique identification , 1972 .

[3]  W. Zachary,et al.  An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.

[4]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[5]  L. Freeman Centrality in social networks conceptual clarification , 1978 .

[6]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[7]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[8]  Albert-László Barabási,et al.  Internet: Diameter of the World-Wide Web , 1999, Nature.

[9]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[10]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

[11]  Alessandro Vespignani,et al.  Epidemic spreading in scale-free networks. , 2000, Physical review letters.

[12]  U. Brandes A faster algorithm for betweenness centrality , 2001 .

[13]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[14]  M E J Newman Assortative mixing in networks. , 2002, Physical review letters.

[15]  A. Barabasi,et al.  Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.

[16]  M. Barthelemy Betweenness centrality in large complex networks , 2003, cond-mat/0309436.

[17]  Luciano da Fontoura Costa,et al.  A graph-based approach for multiscale shape analysis , 2004, Pattern Recognit..

[18]  Heiko Rieger,et al.  Random walks on complex networks. , 2004, Physical review letters.

[19]  L. da F. Costa,et al.  Characterization of complex networks: A survey of measurements , 2005, cond-mat/0505185.

[20]  Mark E. J. Newman A measure of betweenness centrality based on random walks , 2005, Soc. Networks.

[21]  Luciano da Fontoura Costa,et al.  Topographical maps as complex networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Wei Lin,et al.  Complete synchronization of the noise-perturbed Chua's circuits. , 2005, Chaos.

[23]  宁北芳,et al.  疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A , 2005 .

[24]  Albert-László Barabási,et al.  The origin of bursts and heavy tails in human dynamics , 2005, Nature.

[25]  J. A. Rodríguez-Velázquez,et al.  Subgraph centrality in complex networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  Alexandre Wagemakers,et al.  Synchronization of electronic genetic networks. , 2006, Chaos.

[27]  Jianfeng Feng,et al.  Synchronization in networks with random interactions: theory and applications. , 2006, Chaos.

[28]  Edward Ott,et al.  Characterizing the dynamical importance of network nodes and links. , 2006, Physical review letters.

[29]  Alex Arenas,et al.  Synchronization reveals topological scales in complex networks. , 2006, Physical review letters.

[30]  V. Latora,et al.  Complex networks: Structure and dynamics , 2006 .

[31]  M Small,et al.  Complex network from pseudoperiodic time series: topology versus dynamics. , 2006, Physical review letters.

[32]  Lucas Antiqueira,et al.  Correlations between structure and random walk dynamics in directed complex networks , 2007, Applied physics letters.

[33]  Marián Boguñá,et al.  Navigability of Complex Networks , 2007, ArXiv.

[34]  Alessandro Vespignani,et al.  Dynamical Processes on Complex Networks , 2008 .

[35]  M. Small,et al.  Characterizing pseudoperiodic time series through the complex network approach , 2008 .

[36]  Valery Van Kerrebroeck,et al.  Ranking vertices or edges of a network by loops: a new approach. , 2008, Physical review letters.

[37]  Yue Yang,et al.  Complex network-based time series analysis , 2008 .

[38]  Pablo Fernández,et al.  Google’s pagerank and beyond: The science of search engine rankings , 2008 .

[39]  Michael Small,et al.  Superfamily phenomena and motifs of networks induced from time series , 2008, Proceedings of the National Academy of Sciences.

[40]  Martin Rosvall,et al.  Maps of random walks on complex networks reveal community structure , 2007, Proceedings of the National Academy of Sciences.

[41]  Jurgen Kurths,et al.  Synchronization in complex networks , 2008, 0805.2976.

[42]  Michael Small,et al.  Revising the simple measures of assortativity in complex networks. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[43]  R. Rosenfeld Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[44]  M. Small,et al.  Seeding the Kernels in graphs: toward multi-resolution community analysis , 2009 .

[45]  M. Small,et al.  Hub nodes inhibit the outbreak of epidemic under voluntary vaccination , 2010 .

[46]  Yimin Wei,et al.  Matrix Sign Function Methods for Solving Projected Generalized Continuous-Time Sylvester Equations , 2010, IEEE Transactions on Automatic Control.

[47]  Michael Small,et al.  Mapping from structure to dynamics: a unified view of dynamical processes on networks. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[48]  James T. Kwok,et al.  Simplifying Mixture Models Through Function Approximation , 2006, IEEE Transactions on Neural Networks.

[49]  Francisco Aparecido Rodrigues,et al.  Generalized connectivity between any two nodes in a complex network. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[50]  Michael Small,et al.  Rich-club connectivity dominates assortativity and transitivity of complex networks , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.