在复杂网络中传播错误信息的数学框架:取决于拓学的扭曲和控制
Saikat Sur1,2, Rohitashwa Chattopadhyay3, Jens Christian Claussen4
1Optics & Quantum Information Group, The Institute of Mathematical Sciences, HBNI, CIT Campus, Taramani, Chennai 600113, India.
Chaos (Woodbury, N.Y.)
|March 4, 2026
概括
我们开发了一个框架来量化复杂网络中的错误信息. 网络结构显著影响信息扭曲,无规模和小世界网络显示出比随机或常规网络更好的弹性.
科学领域:
- 复杂系统科学 复杂系统科学
- 网络科学 网络科学
- 信息理论 信息理论
背景情况:
- 错误信息在各种系统中广泛传播.
- 由于背景和网络异质性,很难量化网络中的信息扭曲.
- 现有的模型与现实世界的网络复杂性作斗争.
研究的目的:
- 开发一个一般的数学框架来量化分布式系统中的信息扭曲.
- 分析局部错误如何在网络路径上传播和积累.
- 了解各种网络结构中错误信息的拓特征.
主要方法:
- 开发了一个数学框架,模拟沿网络地质测量系统的错误积累.
- 利用二项式噪声的漂移波动分解进行分析.
- 为节点级感知分布衍生闭式表达式.
- 将框架应用于正规图集 (Erdős-Rényi,无尺度,小世界,正规格子).
主要成果:
- 发现了在网络中错误传播的移位不变原理.
- 识别了不同网络拓的不同错误信息配置文件.
- 无规模网络通过枢纽显示错误信息的抑制;小世界网络平衡集群和路径长度.
- 在网络类型的错误信息水平中发现了依赖连接的交叉.
结论:
- 网络拓学极大地影响了信息可靠性和错误信息的传播.
- 稀缺性,结构性组织和连接成本定义了最小误导信息的制度.
- 该框架提供了分析工具,用于理解和控制复杂的网络系统中的信息扭曲.
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