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• W2395439732 abstract "Previous chapter Next chapter Full AccessProceedings Proceedings of the 2012 SIAM International Conference on Data Mining (SDM)Influence Blocking Maximization in Social Networks under the Competitive Linear Threshold ModelXinran He, Guojie Song, Wei Chen, and Qingye JiangXinran He, Guojie Song, Wei Chen, and Qingye Jiangpp.463 - 474Chapter DOI:https://doi.org/10.1137/1.9781611972825.40PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract In many real-world situations, different and often opposite opinions, innovations, or products are competing with one another for their social influence in a networked society. In this paper, we study competitive influence propagation in social networks under the competitive linear threshold (CLT) model, an extension to the classic linear threshold model. Under the CLT model, we focus on the problem that one entity tries to block the influence propagation of its competing entity as much as possible by strategically selecting a number of seed nodes that could initiate its own influence propagation. We call this problem the influence blocking maximization (IBM) problem. We prove that the objective function of IBM in the CLT model is submodular, and thus a greedy algorithm could achieve 1 — 1/e approximation ratio. However, the greedy algorithm requires Monte-Carlo simulations of competitive influence propagation, which makes the algorithm not efficient. We design an efficient algorithm CLDAG, which utilizes the properties of the CLT model, to address this issue. We conduct extensive simulations of CLDAG, the greedy algorithm, and other baseline algorithms on real-world and synthetic datasets. Our results show that CLDAG is able to provide best accuracy in par with the greedy algorithm and often better than other algorithms, while it is two orders of magnitude faster than the greedy algorithm. Previous chapter Next chapter RelatedDetails Published:2012ISBN:978-1-61197-232-0eISBN:978-1-61197-282-5 https://doi.org/10.1137/1.9781611972825Book Series Name:ProceedingsBook Code:PRDT12Book Pages:1-1150Key words:influence blocking maximization, competitive linear threshold model, social networks" @default.
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• W2395439732 date "2012-04-26" @default.
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• W2395439732 title "Influence Blocking Maximization in Social Networks under the Competitive Linear Threshold Model" @default.
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• W2395439732 doi "https://doi.org/10.1137/1.9781611972825.40" @default.
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