Influence maximization is an important research topic which has been extensively studied in various fields. In this paper, a stigmergybased approach has been proposed to tackle the influence maximization problem. We modelled the influence propagation process as ant’s crawling behaviours, and their communications rely on a kind of biological chemicals, i.e., pheromone. The amount of the pheromone allocation is concerning the factors of influence propagation in the social network. The model is capable of analysing influential relationships in a social network in decentralized manners and identifying the influential users more efficiently than traditional seed selection algorithms.
CITATION STYLE
Li, W., Bai, Q., Jiang, C., & Zhang, M. (2016). Stigmergy-based influence maximization in social networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9810 LNCS, pp. 750–762). Springer Verlag. https://doi.org/10.1007/978-3-319-42911-3_63
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