Abstract

We study the interplay between a dynamic process and the structure of the network on which it is defined. Specifically, we examine the impact of this interaction on the quality-measure of network clusters and node centrality. This enables us to effectively identify network communities and important nodes participating in the dynamics. As the first step towards this objective, we introduce an umbrella framework for defining and characterizing an ensemble of dynamic processes on a network. This framework generalizes the traditional Laplacian framework to continuous-time biased random walks and also allows us to model some epidemic processes over a network. For each dynamic process in our framework, we can define a function that measures the quality of every subset of nodes as a potential cluster (or community) with respect to this process on a given network. This subset-quality function generalizes the …

Date

August 24, 2014

Authors

Rumi Ghosh, Shang-hua Teng, Kristina Lerman, Xiaoran Yan

Book

Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining

Pages

1406-1415