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A Tactile Automated Passive-Finger Stimulator TAPS

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Pair approximation for the noisy threshold q-voter model.

Allan R Vieira¹, Antonio F Peralta², Raul Toral²

¹Department of Physics, Pontifical Catholic University of Rio de Janeiro, PUC-Rio, Rua Marquês de São Vicente, 225, 22451-900 Rio de Janeiro, Brazil.

Physical Review. E

|June 25, 2020

Summary

This summary is machine-generated.

This study explores the threshold q-voter model on random networks, finding that network structure impacts opinion dynamics, unlike in mean-field models. Repetition in influence groups significantly alters results on networks.

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Area of Science:

Social dynamics
Statistical physics
Network science

Background:

The standard q-voter model requires full consensus for opinion change.
The threshold q-voter model allows opinion change with partial consensus and nonconformist choices.
Previous studies focused on fully connected (mean-field) networks.

Purpose of the Study:

Investigate the threshold q-voter model dynamics on random networks.
Analyze the impact of allowing or disallowing repetitions within influence groups.
Compare simulation results with pair approximation predictions for uncorrelated networks.

Main Methods:

Agent-based computer simulations of the threshold q-voter model.
Analysis of opinion dynamics on random networks with varying structures.
Application and validation of pair approximation for network models.

Main Results:

Network structure significantly influences opinion dynamics, unlike in the mean-field limit.
The allowance of repetitions in influence groups critically affects model outcomes on networks.
Discrepancies between simulation and pair approximation highlight network complexity.

Conclusions:

The threshold q-voter model exhibits richer dynamics on random networks than previously understood.
Network topology and influence group composition are crucial factors in opinion formation.
Pair approximation provides a useful but limited framework for analyzing complex network dynamics.