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An online game spread model combining key nodes in scale-free networks
Zongzhao Han1, Qian Yu2, Qingfeng Chen2
1School of Computer, Electronics and Information, Guangxi University, Nanning, 530004, China. hzh2023@st.gxu.edu.cn.
Scientific Reports
|February 26, 2025
Summary
Online game addiction spreads through social networks, causing health issues. A new model shows addiction persists when spread rate exceeds recovery, highlighting network dynamics in its propagation.
Area of Science:
- Network Science
- Epidemiology
- Computational Social Science
Background:
- Online game addiction is a growing concern linked to health disorders.
- Social interactions are a key mechanism for the propagation of online game addiction.
- Understanding the spread dynamics in complex networks is crucial.
Purpose of the Study:
- To develop and analyze a mathematical model for online game addiction spread.
- To incorporate key nodes and network structure (scale-free networks) into the model.
- To determine conditions for the persistence or extinction of online game addiction.
Main Methods:
- Development of a Game Player Addiction Epidemic (GPAE) model on scale-free networks.
- Analysis of node degree distribution for local impact assessment.
- Calculation of the basic reproduction number ([Formula: see text]) and equilibrium points.
Main Results:
- The model predicts a stable state with no addiction when [Formula: see text] is below a threshold.
- A unique positive equilibrium point emerges when [Formula: see text] exceeds the threshold, indicating persistent addiction.
- Numerical simulations and real-world data confirm the model's accuracy in representing spread dynamics.
Conclusions:
- The GPAE model provides a robust framework for understanding online game addiction spread.
- Network structure and key nodes significantly influence addiction propagation.
- The basic reproduction number is a critical indicator for predicting the persistence of online game addiction.
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