面向系统免疫:模拟虚假信息传播动态与干预和网络驱动的风险级联
Chunbing Bao1, Haoqian Xie1, Wenting Chen1
1School of Management, Shandong University, Jinan, Shandong, China.
概括
这项研究引入了社交媒体传播虚假信息的新模式,考虑了个人行为和网络结构. 它提供了打击假新闻和增强数字社会的弹性工具.
科学领域:
- 计算社会科学 计算社会科学
- 网络科学 网络科学
- 行为经济学是一种行为经济学.
背景情况:
- 社交媒体上的虚假信息威胁到数字社会,导致认知扭曲和公共危机.
- 现有的模型未能捕捉到个体异质性,完整的理性假设或跨规模风险合.
研究的目的:
- 提出一种新的虚假信息传播模型,整合个人动态,网络拓和干预分析.
- 为虚假信息免疫系统开发一个理论框架,并为数字治理提供可量化的决策工具.
主要方法:
- 构建了一个网络传播模型,结合了风险感知,决策灵敏度和认知惯性.
- 开发了一个双指数系统,根据风险暴露和脆弱性来识别超级传播者.
- 制定了一个干预模型,将认知纠正和传播抑制结合起来,分析平衡和趋同.
主要成果:
- 在非干预模型中证明了平衡的存在,并在干预中获得了独特的趋同条件.
- 确立了有限干预效率定理,并推导了对收时间的下限.
- 通过个人异质性和干预强度量化系统性风险的联合调制.
结论:
- 拟议的模型提供了一个全面的框架,用于理解和减轻虚假信息的传播.
- 调查结果为数字治理提供了可量化的工具,增强了对虚假新闻带来的系统风险的抵御力.
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