论文标题
关于用于建模多重传染的独立网络的局限性
On limitations of uniplex networks for modeling multiplex contagion
论文作者
论文摘要
许多网络传染过程本质上是本质上的多重多重过程，但通常会减少到分析实践中单流网络上的过程。因此，我们研究了数据建模选择如何影响传染过程的预测。我们证明，多重传染过程不仅是传染过程对其组成的单流网络的结合。我们使用来自两个不同环境的多重网络数据 - （1）行为网络使用“简单”的流行病学模型来代表其传染病传播的潜力，以及（2）在线社交网站的用户使用基于阈值的“复杂”传播过程来表示其信息传播的潜力。我们的结果表明，即使将它们组合起来，也不会准确地捕获多重数据的传播，并且（组合）独立和多路复用结果之间的差异性质取决于这些网络上的特定传播过程。
Many network contagion processes are inherently multiplex in nature, yet are often reduced to processes on uniplex networks in analytic practice. We therefore examine how data modeling choices can affect the predictions of contagion processes. We demonstrate that multiplex contagion processes are not simply the union of contagion processes over their constituent uniplex networks. We use multiplex network data from two different contexts -- (1) a behavioral network to represent their potential for infectious disease transmission using a "simple" epidemiological model, and (2) users from online social network sites to represent their potential for information spread using a threshold-based "complex" contagion process. Our results show that contagion on multiplex data is not captured accurately in models developed from the uniplex networks even when they are combined, and that the nature of the differences between the (combined) uniplex and multiplex results depends on the specific spreading process over these networks.
