A multi-layer dynamic model of information propagation considering individual three-phase linear modulated behaviors

The propagation of individual behaviors has emerged as a significant phenomenon influencing social trust and stability. To thoroughly investigate this, we propose a multi-layer dynamic model that captures non-monotonic responses in behavior spread. This model highlights that behavioral intensity is suppressed in the middle state interval but promoted in the low and high state intervals, employing a threshold modeling approach. We perform a detailed mathematical analysis of the dynamics of individual behaviors using a three-phase linear modulation (TPLM), developing an edge-based compartmental theory that aligns remarkably well with simulation results. Our analysis and numerical simulations reveal that these modulated behaviors significantly impact dynamics, as measured by the final adoption size. Notably, we observe a phenomenon in the order of the phase transition from second-order continuous to first-order discontinuous, mediated by the behavioral parameters. This transition can be triggered by adjusting parameters and structural perturbations, such as altering individuals’ adoption thresholds or increasing network heterogeneity. • This study examines TPLM dynamics via non-monotonic spread in double-layer networks. • The threshold model with TPLM behaviors is established. • The behavioral threshold is proposed by a N-shaped probability function. • The phase transition on final adoption size is affected by TPLM behaviors.

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Publication Details

Journal
Physica A Statistical Mechanics and its Applications
Published
2026-03-05
DOI
https://doi.org/10.1016/j.physa.2026.131427
Primary Topic
Theoretical and Computational Physics
Type
article
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article

A multi-layer dynamic model of information propagation considering individual three-phase linear modulated behaviors

Hui Fang Tian, Yang Tian
Physica A Statistical Mechanics and its Applications
Theoretical and Computational Physics
article

A multi-layer dynamic model of information propagation considering individual three-phase linear modulated behaviors

Hui Fang Tian, Yang Tian
article en

Abstract

The propagation of individual behaviors has emerged as a significant phenomenon influencing social trust and stability. To thoroughly investigate this, we propose a multi-layer dynamic model that captures non-monotonic responses in behavior spread. This model highlights that behavioral intensity is suppressed in the middle state interval but promoted in the low and high state intervals, employing a threshold modeling approach. We perform a detailed mathematical analysis of the dynamics of individual behaviors using a three-phase linear modulation (TPLM), developing an edge-based compartmental theory that aligns remarkably well with simulation results. Our analysis and numerical simulations reveal that these modulated behaviors significantly impact dynamics, as measured by the final adoption size. Notably, we observe a phenomenon in the order of the phase transition from second-order continuous to first-order discontinuous, mediated by the behavioral parameters. This transition can be triggered by adjusting parameters and structural perturbations, such as altering individuals’ adoption thresholds or increasing network heterogeneity. • This study examines TPLM dynamics via non-monotonic spread in double-layer networks. • The threshold model with TPLM behaviors is established. • The behavioral threshold is proposed by a N-shaped probability function. • The phase transition on final adoption size is affected by TPLM behaviors.

Physica A Statistical Mechanics and its ApplicationsVol. 689
Beijing University of Posts and Telecommunications (CN), Beijing Information Science & Technology University (CN)
Openalex Percentile: Top 32%
Theoretical and Computational Physics
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