A Dynamic Vote-Rank Based Approach for Effective Sequential Initialization of Information Spreading Processes Within Complex Networks

Seed selection is one of the key factors influencing information spread within networks. Whereas most solutions are based on single-stage seeding at the beginning of the process, performance increases when additional seeds are used. This enables the acquisition of knowledge about ongoing processes and activating new nodes for further influence maximisation. This paper describes an approach based on the Vote-Rank algorithm with dynamic rankings for sequential seed selection. The results prove the increased performance of dynamic rankings compared to the static version and show how the frequency of ranking updates affects both performance and computational costs.