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An algorithm for critical nodes problem in social networks based on Owen value.

Xue-Guang Wang1

  • 1Department of Computer Science, East China University of Political Science and Law, Shanghai 201620, China ; Department of Computer Science, University College London (UCL), London WC1E 6BT, UK.

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|July 10, 2014
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Summary
This summary is machine-generated.

Identifying critical nodes in social networks is crucial. This study introduces a novel method using Owen values to pinpoint these key nodes, effectively analyzing network structures and validating its performance on diverse datasets.

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Area of Science:

  • Social network analysis
  • Graph theory
  • Network science

Background:

  • Identifying critical nodes is essential for understanding social network dynamics and applications.
  • Existing methods may not fully account for complex community structures within networks.

Purpose of the Study:

  • To develop a novel method for discovering critical nodes in social networks.
  • To incorporate the influence of community structures into node criticality assessment.

Main Methods:

  • Calculating each node's marginal contribution using the Owen value.
  • Applying the Owen value-based method to identify critical nodes in social networks.

Main Results:

  • The proposed method effectively identifies critical nodes across synthetic and real-world social network datasets.
  • Validation on six real datasets and two synthetic datasets demonstrates the method's feasibility and effectiveness.
  • Analysis of a terrorist network using this method yielded results consistent with known information.

Conclusions:

  • The Owen value-based approach provides a robust solution for the critical node problem in social networks.
  • This method enhances the understanding of network structures by considering community influences.
  • The findings have practical implications for network analysis, including security and information dissemination.