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  • 标题:Minimizing the Influence Propagation in Social Networks for Linear Threshold Models
  • 本地全文:下载
  • 作者:Lan Yang ; Alessandro Giua ; Zhiwu Li
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2017
  • 卷号:50
  • 期号:1
  • 页码:14465-14470
  • DOI:10.1016/j.ifacol.2017.08.2293
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractInnovation or information propagation in social networks has been widely studied in recent years. Most of the previous works are focused on solving the problem of influence maximization, which aims to identify a small subset of early adopters in a social network to maximize the influence propagation under a given diffusion model. In this paper, motivated by practical scenarios, we propose two different influence minimization problems. We consider a Linear Threshold diffusion model and provide a general solution to the first problem solving a linear integer programming. For the second problem, we provide a technique to search for an optimal solution that works only in particular cases and discuss a simple heuristic to find a solution in the general case.
  • 关键词:KeywordsSocial networkOptimizationInfluence propagationLinear Threshold model
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