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The Research and Design of Algorithm for Influence Maximization in Social Networks Based on Activity ⋆

Influence maximization problem is how to select a set of seed nodes and then maximize the dissemination of information according to some strategies in social networks. In this paper, we introduce the node activity into the IC model and then propose the AIC (activity independent cascade) model and the corresponding heuristic algorithm ACH which narrows the range of primaries and improves the quality of candidate nodes by considering node activity attributes. Our simulation results also show its superiorityACH is close to KK on influence scope while better than other heuristic algorithms on timeliness, which manifests the applicability of AIC for large social networks.