Abstract

We investigate the problem of influence maximization in a social network. Building on the widely used threshold diffusion model where each node has a threshold and is activated when the influence it receives is above the threshold, we define a critical threshold vector as a vector (consisting of the thresholds for all nodes) that guarantees influence spreading to the entire network, but any larger threshold vector would result in spreading to only part of the network. We show that a critical threshold vector can be translated to a graph coloring, based on which we establish a necessary condition for influence maximization. Further, we propose a k-neighborhood decomposition method to construct a critical threshold vector, and show that this method can be used to find a large family of critical threshold vectors. We also explore the connection between critical threshold vectors and graph orientations, as well as the properties of the k-neighborhood decomposition.

Original languageEnglish (US)
Title of host publication2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
DOIs
StatePublished - Nov 12 2012
Event2012 46th Annual Conference on Information Sciences and Systems, CISS 2012 - Princeton, NJ, United States
Duration: Mar 21 2012Mar 23 2012

Publication series

Name2012 46th Annual Conference on Information Sciences and Systems, CISS 2012

Other

Other2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
CountryUnited States
CityPrinceton, NJ
Period3/21/123/23/12

Keywords

  • Critical Threshold Vector
  • Influence Spreading
  • Social Network

ASJC Scopus subject areas

  • Information Systems

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