School of Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts, 02215, USA.
Sci Rep. 2017 Jul 21;7(1):6103. doi: 10.1038/s41598-017-06286-w.
Understanding the spreading mechanisms of social contagions in complex network systems has attracted much attention in the physics community. Here we propose a generalized threshold model to describe social contagions. Using extensive numerical simulations and theoretical analyses, we find that a hysteresis loop emerges in the system. Specifically, the steady state of the system is sensitive to the initial conditions of the dynamics of the system. In the steady state, the adoption size increases discontinuously with the transmission probability of information about social contagions, and trial size exhibits a non-monotonic pattern, i.e., it first increases discontinuously then decreases continuously. Finally we study social contagions on heterogeneous networks and find that network topology does not qualitatively affect our results.
理解复杂网络系统中社会传播的扩散机制在物理学界引起了广泛关注。在这里，我们提出了一个广义阈值模型来描述社会传播。通过广泛的数值模拟和理论分析，我们发现系统中出现了滞后环。具体来说，系统的稳态对系统动力学的初始条件很敏感。在稳定状态下，采用规模随着社会传播信息的传输概率的增加而不连续地增加，而试用规模则呈现出非单调的模式，即它先是不连续地增加，然后连续地减少。最后，我们研究了异质网络上的社会传播，发现网络拓扑结构并没有从本质上影响我们的结果。
