Abstract
Influence maximization is an important research topic which has been extensively studied in various fields. In this paper, a stigmergy-based 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.
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Li, W., Bai, Q., Jiang, C., Zhang, M. (2016). Stigmergy-Based Influence Maximization in Social Networks. In: Booth, R., Zhang, ML. (eds) PRICAI 2016: Trends in Artificial Intelligence. PRICAI 2016. Lecture Notes in Computer Science(), vol 9810. Springer, Cham. https://doi.org/10.1007/978-3-319-42911-3_63
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DOI: https://doi.org/10.1007/978-3-319-42911-3_63
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