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Updated: Jul 14, 2025

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Trust levels in social networks.

Santanu Acharjee1, Akhil Thomas Panicker2

  • 1Department of Mathematics, Gauhati University, Assam, India.

Heliyon
|October 9, 2023
PubMed
Summary
This summary is machine-generated.

As social networks grow, trust levels must increase to maintain stability. Trust does not accelerate information diffusion towards Dunbar's number (150) or hierarchical layers.

Keywords:
Dunbar's numberEvolutionary biologyNeocortexPower-law distributionPower-law exponentSocial networksTrustUniform distribution

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Area of Science:

  • Social Network Analysis
  • Cognitive Science
  • Sociology

Background:

  • Dunbar's number defines the cognitive limit for stable social relationships, linked to neocortex size.
  • Trust is crucial for selecting network members and network evolution over time.
  • Trust and Dunbar's number are interconnected for maintaining stable social networks.

Purpose of the Study:

  • Investigate if trust levels change with increasing network size.
  • Determine the relationship between the power-law exponent and trust cutoff.
  • Assess if trust facilitates information diffusion towards Dunbar's number and hierarchical layers.

Main Methods:

  • Analysis of social network dynamics.
  • Examination of trust formation and its impact on network size.
  • Exploration of information diffusion patterns within hierarchical network structures.

Main Results:

  • Trust levels must increase among existing individuals as network size expands.
  • A relationship exists where the power-law exponent is inversely proportional to the trust cutoff.
  • Trust levels do not accelerate information diffusion towards Dunbar's number (150) or predefined hierarchy layers (5, 15, 50).

Conclusions:

  • Maintaining stable, larger social networks necessitates enhanced trust among individuals.
  • The findings provide insights into the complex interplay between cognitive limits, trust, and network structure.
  • Trust's role in information spread within structured social networks is less significant than previously assumed.