Influence of activity-state transitions on emotion propagation

Activity as an individual trait has a profound impact on social group behavior and emotion propagation. Based on this, this paper proposes a new two-layer network model of emotion propagation, named \({N}_AA{N}_A - S{P}_ER\) model. In this model, the upper layer is an activity-state transition subnet including higher-order interactions characterized by simplicial complexes, while the lower layer is an emotion propagation subnet with binary interactions. Combined microscopic Markov Chain approach (MMCA) with SIS and SIR epidemic spreading model, this paper establishes some emotion dynamics evolution equations for the \({N}_AA{N}_A - S{P}_ER\) model newly proposed. Abundant Monte Carlo (MC) simulations and MMCA numerical simulations validate the feasibility and effectiveness of the theoretical analysis results. In addition, appropriately reducing activation probability, high-order activation probability, or infection decay factor, can hinder emotion propagation, as well as properly increasing degradation probability or high-order degradation probability.