Max Planck Institute for Dynamics and Self-Organization -- Department for Nonlinear Dynamics and Network Dynamics Group
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BFNT/BCCN Sonderseminar

Tuesday, 01.03.2011 15 c.t.

Eigenvector centrality as a predictor of nodes' influence on network dynamics

by Dr. Konstantin Klemm
from Bioinformatik, Uni Leipzig

Contact person: Jan Nagler


Seminarraum Haus 2, 4. Stock (Bunsenstr.)


Identifying key players in collective dynamics remains a challenge affecting a great variety of research fields, from the efficient dissemination of ideas to drug target discovery in biomedical problems. The difficulty lies at several levels: how to single out the role of individual elements in such intermingled systems, or which is the best way to quantify their importance. Centrality measures aim at capturing the influence of a node from its position in a network. The key issue obviated is that the contribution of a node to the collective behavior is not uniquely determined by the structure of the system but it is a result of the interplay between dynamics and network structure. Here we show that dynamical influence measures explicitly how strongly a node's dynamical state affects collective behavior [1]. For diffusive processes in complex networks, dynamical influence quantifies how efficiently real systems may be driven by manipulating the state of single nodes. For critical spreading, it targets nodes with superior spreading capabilities. [1] Klemm et al., e-print arXiv:1002.4042v2

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