Group evolving dynamics in biased condition: modeling and analysis

TL;DR

This paper introduces a nonlinear dynamical model for group formation influenced by biases, analyzing stability and equilibrium conditions through theoretical derivations and simulations.

Contribution

It presents a novel model incorporating bias-modulated attraction functions for group dynamics, with analytical and simulation-based analysis of equilibrium stability.

Findings

System converges to stable equilibria under certain conditions

Bias strength significantly affects group size distribution

Rich nonlinear behaviors observed with varying parameters

Abstract

We propose a dynamical model for group formation and switching behavior in systems where each group competes for members through attraction functions that are inversely proportional to their current sizes. This attraction is modulated by group-specific bias terms, which can reflect social, economic, or reputational advantages. New entrants choose groups probabilistically based on these weighted attraction scores. We derive the conditions under which the system converges to a stationary equilibrium, where group proportions remain stable over time. The model exhibits rich nonlinear behavior, especially under varying bias strengths and inverse preference intensities. We analyze equilibrium conditions both theoretically and via simulations.