在复杂的网络上,信息格局的粗化与不对称的社会传染过程在复杂的网络上
Haechan Seo1, Soon-Hyung Yook1
1Kyung Hee University, Department of Physics and Research Institute for Basic Sciences, Seoul 02447, Korea.
Physical review. E
|December 23, 2025
概括
本研究研究了网络结构如何使用社会传染模型影响信息多样性. 我们发现,随着网络复杂度的增加,无规模网络呈现出向更顺的信息传播过渡.
科学领域:
- 复杂的系统复杂的系统.
- 网络科学 网络科学
- 信息理论 信息理论
背景情况:
- 了解在现实世界网络中传播的信息至关重要.
- 交互拓和竞争对信息多样性的影响很大.
- 哈尔沃森-佩德森-斯内 (HPS) 模型为研究社会传染提供了一个框架.
研究的目的:
- 分析交互拓对HPS社会传染模型中的信息多样性的影响.
- 调查竞争如何影响不同网络结构的信息多样性.
- 为了量化信息多样性,使用信息值的平方根平均值 (W(N,t)).
主要方法:
- 在静态复杂网络上对HPS模型的数值模拟.
- 信息多样性的分析,用W{\displaystyle W{\displaystyle N} ,t测量,类似于粗现象中的接口宽度.
- 检查网络属性,包括Erdős-Rényi随机网络和具有不同度指数 (γ) 的无尺度网络.
主要成果:
- 在Erdős-Rényi网络上的HPS模型始终保持在平滑阶段 (粗指数α=0).
- 在无尺度网络上,随着度指数 γ 的增加,从粗阶段 (α>0) 过渡到光滑阶段.
- 这种过渡的关键值在γ*4时被确定,稳定状态W(N,t) 的缩放为W_{sat}(N)∼logN在γ=4.
结论:
- 网络拓学批判性地决定了HPS模型内的信息多样性的阶段过渡.
- 无尺度网络表现出一个过渡到更顺的信息传播超出特定度指数值.
- 这些发现有助于理解复杂系统中的信息动态,并提供对网络稳定性和信息传播的见解.
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