Literature DB >> 36093057

Social diffusion sources can escape detection.

Marcin Waniek1, Petter Holme2,3, Manuel Cebrian4,5,6, Talal Rahwan1.   

Abstract

Influencing 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.
© 2022 The Authors.

Entities:  

Keywords:  Applied sciences; Computer science; Computer systems organization; Internet; Internet-based information systems; Social sciences

Year:  2022        PMID: 36093057      PMCID: PMC9459693          DOI: 10.1016/j.isci.2022.104956

Source DB:  PubMed          Journal:  iScience        ISSN: 2589-0042


  21 in total

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Journal:  Science       Date:  1999-10-15       Impact factor: 47.728

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5.  Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world.

Authors:  Per Block; Marion Hoffman; Isabel J Raabe; Jennifer Beam Dowd; Charles Rahal; Ridhi Kashyap; Melinda C Mills
Journal:  Nat Hum Behav       Date:  2020-06-04

6.  How to Hide One's Relationships from Link Prediction Algorithms.

Authors:  Marcin Waniek; Kai Zhou; Yevgeniy Vorobeychik; Esteban Moro; Tomasz P Michalak; Talal Rahwan
Journal:  Sci Rep       Date:  2019-08-21       Impact factor: 4.379

7.  Identification of Patient Zero in Static and Temporal Networks: Robustness and Limitations.

Authors:  Nino Antulov-Fantulin; Alen Lančić; Tomislav Šmuc; Hrvoje Štefančić; Mile Šikić
Journal:  Phys Rev Lett       Date:  2015-06-16       Impact factor: 9.161

8.  The anatomy of a scientific rumor.

Authors:  M De Domenico; A Lima; P Mougel; M Musolesi
Journal:  Sci Rep       Date:  2013-10-18       Impact factor: 4.379

9.  Reconstructing propagation networks with natural diversity and identifying hidden sources.

Authors:  Zhesi Shen; Wen-Xu Wang; Ying Fan; Zengru Di; Ying-Cheng Lai
Journal:  Nat Commun       Date:  2014-07-11       Impact factor: 14.919

10.  Diffusion in Colocation Contact Networks: The Impact of Nodal Spatiotemporal Dynamics.

Authors:  Bryce Thomas; Raja Jurdak; Kun Zhao; Ian Atkinson
Journal:  PLoS One       Date:  2016-08-08       Impact factor: 3.240

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