Machine learningNetwork science
贝叶斯网络扩散分析
贝叶斯网络扩散分析将贝叶斯概率推断应用于研究信息、疾病、行为或创新如何在网络中传播。通过为扩散参数设置先验并用观察到的级联数据更新它们，该方法在一个原则性的统计框架内量化传播速率、识别有影响力的传播者、重建潜在的传播路径，并提供完整的不确定性估计。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Gomez Rodriguez, M., Leskovec, J., & Scholkopf, B. (2012). Structure and Dynamics of Information Pathways in Online Media. Proceedings of the 6th ACM International Conference on Web Search and Data Mining (WSDM), 23–32. DOI: 10.1145/2433396.2433402 ↗
- Kitsak, M., Gallos, L. K., Havlin, S., Liljeros, F., Muchnik, L., Stanley, H. E., & Makse, H. A. (2010). Identification of influential spreaders in complex networks. Nature Physics, 6(11), 888–893. DOI: 10.1038/nphys1746 ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Network Diffusion Analysis (Probabilistic Inference on Contagion and Spreading Processes). ScholarGate. https://scholargate.app/zh/network-analysis/bayesian-network-diffusion-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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