Efficient heuristic algorithms for positive-influence dominating set in social networks

With the ongoing growth of social networks, individuals are obtaining a platform from which they can spread their opinions and ideas without restrictions and without noticing we are allowing those opinions to influence our sociological, political, and personal opinions. It is now much easier to broadcast an idea that has a potential to widely spread positive or negative influence across a social network. In an attempt to address influence in this context, the notion of a “positive influence dominating set” appeared recently: a positive influence dominating set in a graph, or network, is a set of nodes D such that every other node has a sufficient percentage of neighbors in D. The corresponding optimization problem seeks a positive influence dominating set of minimum size. In this paper we present and study efficient heuristic algorithms for the problem and show how different types of social networks/graphs require different heuristic methods to effectively extract positive influence dominating sets.

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