Impact of temporal network structures on the speed of consensus formation in opinion dynamics
Mingwu Li, Harry Dankowicz

TL;DR
This study investigates how temporal network structures influence the speed of consensus formation in opinion dynamics, revealing that static models overestimate speed and that temporal patterns like burstiness have minimal impact.
Contribution
It demonstrates the significant effects of temporal patterns and node lifetimes on consensus speed, highlighting limitations of static network assumptions in opinion dynamics models.
Findings
Static networks overestimate consensus speed.
Weight heterogeneity inhibits consensus formation.
Node lifetime variability significantly affects consensus speed.
Abstract
Opinion dynamics on networks has wide applications to empirical and engineered systems and profound prospects in the general study of complex systems. Many efforts have been devoted to understanding how opinion dynamics is affected by network topology. However, human social interactions are best characterized as temporal networks in which ordering of interactions cannot be ignored. Temporal activity patterns including heterogeneous contact strength and interevent times, turnover edge/node dynamics and daily patterns could have significant effects that would not be captured by static aggregate network representations. In this paper, we study the effects of such temporal patterns on the speed of consensus formation in various models of continuous opinion dynamics using three empirical human face-to-face networks from different real-world settings. We find that static, aggregated networks…
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