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在COVID-19大流行中模拟情绪传染:一个复杂的网络方法
Yanchun Zhu1, Wei Zhang2, Chenguang Li3
1Business School, Beijing Normal University, Beijing, China.
PeerJ. Computer science
|December 11, 2023
概括
公共卫生危机需要理解情绪传染. 这项研究引入了一个复杂的网络模型来分析情绪如何传播,揭示了影响传染动态和强度的关键因素.
科学领域:
- 流行病学 流行病学
- 网络科学 网络科学
- 社会心理学 社会心理学
背景情况:
- 公共卫生危机需要了解情绪传染的动态.
- 之前的研究集中在消极情绪上,忽视了积极/消极的相互作用.
- 情绪在细化流行病战略中的作用在理论上是显著的.
研究的目的:
- 基于复杂的网络原则,开发和分析一种增强的情绪传染模型.
- 研究各种速率 (感染,煽动,净化,退化,免疫) 对情绪传染的影响.
- 用不同的网络结构来评估模型的性能.
主要方法:
- 开发了一种增强的情绪传染模型,将降解率指数集成到一个复杂的网络框架中.
- 对拟议模型进行稳定性分析.
- 通过实验评估了使用瓦茨-斯特罗格茨小世界,巴拉巴西-阿尔伯特无尺度和新浪微博网络结构的模型.
主要成果:
- 感染率主要决定了情绪传染的速度.
- 煽动和净化速度决定了情绪传染的方向.
- 降解率影响情绪衰退;免疫率影响平衡比例.
- 增加的初始传播者和节点程度放大了传染率,峰值和影响.
结论:
- 改进的模型提供了关于公共卫生危机期间情绪传染动态的见解.
- 关键参数显著调节了情绪传播的速度,方向和强度.
- 这些发现可以为管理流行病中公众情绪反应的策略提供信息.
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