2015/07/31 by Marina Diakonova, Vincenzo Nicosia, Vito Latora +1 · 2 citations
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Degree (music) #Fraction (chemistry) #Function (biology) #Irreducibility #Multiplex #Nonlinear system #Opinion Dynamics and Social Influence #State (computer science) #Theoretical and Computational Physics #Voter model #cond-mat.stat-mech #cs.SI #nlin.AO #physics.soc-ph
paper · pdf · doi:10.1088/1367-2630/18/2/023010
published as New J. Phys. 18, 023010 (2016) · 10 pages, 6 figures
arxiv created 2015/07/31 · openalex publication_date 2016/01/29 · arxiv updated 2016/02/08 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
We address the issue of the reducibility of the dynamics on a multilayer network to an equivalent process on an aggregated single-layer network. As a typical example of models for opinion formation in social networks, we implement the voter model on a two-layer multiplex network, and we study its dynamics as a function of two control parameters, namely the fraction of edges simultaneously existing in both layers of the network (edge overlap), and the fraction of nodes participating in both layers (interlayer connectivity or degree of multiplexity). We compute the asymptotic value of the number of active links (interface density) in the thermodynamic limit, and the time to reach an absorbing state for finite systems, and we compare the numerical results with the analytical predictions on equivalent single-layer networks obtained through various possible aggregation procedures. We find a large region of parameters where the interface density of large multiplexes gives systematic deviations from that of the aggregates. We show that neither of the standard unweighted aggregation procedures is able to capture the highly nonlinear increase in the lifetime of a finite size multiplex at small interlayer connectivity. These results indicate that multiplexity should be appropriately taken into account when studying voter model dynamics, and that, in general, single-layer approximations might be not accurate enough to properly understand processes occurring on multiplex networks, since they might flatten out relevant dynamical details.