Consensus on Dynamic Stochastic Block Models: Fast Convergence and Phase Transitions

TL;DR

This paper studies how opinions evolve in time-varying networks with community structure, proving rapid consensus under certain conditions and identifying phase transitions in convergence behavior.

Contribution

It introduces models of opinion dynamics on evolving stochastic block models, proving fast convergence results and characterizing phase transitions based on initial conditions.

Findings

Any initial bias favors eventual consensus regardless of network size.

Identifies thresholds for initial advantage that determine convergence speed.

Establishes phase transition between rapid consensus and halted dynamics.

Abstract

We introduce two models of consensus following a majority rule on time-evolving stochastic block models (SBM), in which the network evolution is Markovian or non-Markovian. Under the majority rule, in each round, each agent simultaneously updates his/her opinion according to the majority of his/her neighbors. Our network has a community structure and randomly evolves with time. In contrast to the classic setting, the dynamics is not purely deterministic, and reflects the structure of SBM by resampling the connections at each step, making agents with the same opinion more likely to connect than those with different opinions. In the \emph{Markovian model}, connections between agents are resampled at each step according to the SBM law and each agent updates his/her opinion via the majority rule. We prove a \emph{power-of-one} type result, i.e., any initial bias leads to a non-trivial advantage of winning in the end, uniformly in the size of the network. In the \emph{non-Markovian model}, a connection between two agents is resampled according to the SBM law only when some of the two changes opinion and is otherwise kept the same. We study the phase transition between the fast convergence to the consensus and a halt of the dynamics. Moreover, we establish thresholds of the initial lead for various convergence speeds.