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Nonconsensus opinion model on directed networks.

Bo Qu1, Qian Li2, Shlomo Havlin3

  • 1Delft University of Technology, Delft 2628CD, Netherlands.

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Summary
This summary is machine-generated.

In directed social networks, increased link directionality and in-degree/out-degree correlation strengthen majority opinions. This reduces the survival chances for minority viewpoints in opinion dynamics.

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Area of Science:

  • Complex Systems
  • Social Network Analysis
  • Opinion Dynamics

Background:

  • Traditional opinion models often focus on undirected networks and consensus.
  • Real-world networks (e.g., web, social media) are frequently directed with mixed link types.
  • Multiple competing opinions are common in real-world decision-making scenarios.

Purpose of the Study:

  • To investigate a nonconsensus opinion model on directed networks.
  • To analyze the impact of network directionality and degree correlations on opinion competition.

Main Methods:

  • Studied the nonconsensus opinion model by Shao et al. on directed networks.
  • Defined network directionality (ξ) as the proportion of unidirectional links.
  • Quantified in-degree and out-degree relationship using linear correlation coefficient (ρ).
  • Employed two degree-preserving rewiring methods to construct networks with varied ξ and ρ.

Main Results:

  • Higher directionality (ξ) leads to increased dominance of the majority opinion.
  • Increased linear correlation (ρ) between in-degree and out-degree also favors the majority opinion.
  • Minority opinions face reduced survival probability as ξ and ρ increase.

Conclusions:

  • Network structure, specifically directionality and degree correlation, significantly influences opinion dynamics.
  • Directed networks and correlated degrees can suppress opinion diversity.
  • Findings have implications for understanding information spread and opinion formation in real-world networks.