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Rumor spreading dynamics change drastically when the required number of believers (m) increases from 1 to 2. A higher threshold (m≥2) prevents rumors from spreading widely, unlike the rapid spread seen with m=1.

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Area of Science:

  • Social dynamics
  • Information diffusion
  • Computational social science

Background:

  • Understanding rumor propagation is crucial for managing information flow in social networks.
  • Existing models often simplify agent interactions and belief dynamics.

Purpose of the Study:

  • To investigate the impact of group dynamics on rumor spreading.
  • To identify critical thresholds influencing rumor propagation.
  • To explain variations in rumor spread across different social groups.

Main Methods:

  • Agent-based modeling with three agent types: Seeds (initiators), Agnostics (rejectors), and Others (susceptible).
  • Local updates within randomly formed groups.
  • Modeling belief conversion based on the proportion of believers (m).
  • Incorporating a fixed rate (d) for believers becoming indifferent.

Main Results:

  • A threshold effect was observed: increasing the required believers (m) from 1 to ≥2 significantly alters rumor spread.
  • With m=1, rumors spread rapidly, convincing a large portion of the community.
  • With m≥2, even substantial initial believer fractions lead to rumor extinction within a few rounds.

Conclusions:

  • The parameter 'm' (minimum believers for conversion) is a critical factor in rumor dynamics.
  • This model explains why some rumors spread in specific groups but not others.
  • The findings offer insights into the resilience and vulnerability of social networks to misinformation.