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In this paper we analyze influence maximization in the voter model with anactive strategic and a passive influencing party in non-stationary settings. Wethus explore the dependence of optimal influence allocation on the timehorizons of the strategic influencer. We find that on undirected heterogeneousnetworks, for short time horizons, influence is maximized when targetinglow-degree nodes, while for long time horizons influence maximization isachieved when controlling hub nodes. Furthermore, we show that for short andintermediate time scales influence maximization can exploit knowledge of(transient) opinion configurations. More in detail, we find two rules. First,nodes with states differing from the strategic influencer's goal should betargeted. Second, if only few nodes are initially aligned with the strategicinfluencer, nodes subject to opposing influence should be avoided, but whenmany nodes are aligned, an optimal influencer should shadow opposing influence.

Effects of Time Horizons on Influence Maximization in the Voter Dynamics