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  • 标题:Social diffusion sources can escape detection
  • 本地全文:下载
  • 作者:Marcin Waniek ; Petter Holme ; Manuel Cebrian
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2022
  • 卷号:25
  • 期号:9
  • 页码:1-21
  • DOI:10.1016/j.isci.2022.104956
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryInfluencing others through social networks is fundamental to all human societies. Whether this happens through the diffusion of rumors, opinions, or viruses, identifying the diffusion source (i.e., the person that initiated it) is a problem that has attracted much research interest. Nevertheless, existing literature has ignored the possibility that the source might strategically modify the network structure (by rewiring links or introducing fake nodes) to escape detection. Here, without restricting our analysis to any particular diffusion scenario, we close this gap by evaluating two mechanisms that hide the source—one stemming from the source’s actions, the other from the network structure itself. This reveals that sources can easily escape detection, and that removing links is far more effective than introducing fake nodes. Thus, efforts should focus on exposing concealed ties rather than planted entities; such exposure would drastically improve our chances of detecting the diffusion source.Graphical abstractDisplay OmittedHighlights•We study the problem of hiding the diffusion source from source detection algorithms•Finding an optimal way of hiding the source is usually computationally intractable•In many cases, the source is well hidden without any strategic modifications•If the source is exposed, simple heuristic solutions allow it to avoid detectionApplied sciences; Computer science; Internet-based information systems; Computer systems organization; Internet; Social sciences
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