Modeling emotional contagion in the COVID-19 pandemic: a complex network approach

PeerJ Comput Sci. 2023 Nov 20:9:e1693. doi: 10.7717/peerj-cs.1693. eCollection 2023.

Abstract

During public health crises, the investigation into the modes of public emotional contagion assumes paramount theoretical importance and has significant implications for refining epidemic strategies. Prior research predominantly emphasized the antecedents and aftermath of emotions, especially those of a negative nature. The interplay between positive and negative emotions, as well as their role in the propagation of emotional contagion, remains largely unexplored. In response to this gap, an emotional contagion model was developed, built upon the foundational model and enriched from a complex network standpoint by integrating a degradation rate index. Stability analyses of this model were subsequently conducted. Drawing inspiration from topological structural features, an enhanced model was introduced, anchored in complex network principles. This enhanced model was then experimentally assessed using Watts-Strogatz's small-world network, Barabási-Albert's scale-free network, and Sina Weibo network frameworks. Results revealed that the rate of infection predominantly dictates the velocity of emotional contagion. The incitement rate and purification rate determine the overarching direction of emotional contagion, whereas the degradation rate modulates the waning pace of emotions during intermediate and later stages. Furthermore, the immunity rate was observed to influence the proportion of each state at equilibrium. It was discerned that a greater number of initial emotional disseminators, combined with a larger initial contagion node degree, can amplify the emotion contagion rate across the social network, thus augmenting both the peak and overall influence of the contagion.

Keywords: Complex network; Emotional contagion; Infectious disease model; Social network.

Grants and funding

This work is supported by the National Natural Science Foundation of China (Grant number: 72061147005; 71874215; 72004244; 71571191), the National Social Science Foundation of China (Grant number: 21BZZ108), the Beijing Natural Science Foundation (Grant number: 9182016; 9194031); the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Grant number: 17YJAZH120; 19YJCZH253), the Fundamental Research Funds for the Central Universities (SKZZY2015021) and the Political Education Special Fund in Central University of Finance and Economics (“Diffusion mechanism and synergistic analysis of epidemic prevention policies during COVID-19 epidemics”, SZJ2208). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.