论文标题
网络上竞争信息的扩散动态
Diffusion dynamics of competing information on networks
论文作者
论文摘要
社交网络上的信息扩散已被描述为阈值模型框架中阈值行为的集体结果。但是，由于现有模型没有考虑到个人的优化问题，因此当个人面对多个（甚至可能是不兼容的）信息时，在扩散过程中出现了什么动态。在这里，我们开发了一个微型基础的通用阈值模型，使我们能够分析多个信息传播中个体行为的集体动态。分析表明，竞争信息的病毒性从根本上是不确定的。当个体最大程度地与邻居进行协调时，扩散过程被描述为鞍径，从而导致无法预测的对称性破裂。当个人的选择是不可逆转的时，就会有一个稳定的平衡，其中一定程度的社会两极分化发生了。
Information diffusion on social networks has been described as a collective outcome of threshold behaviors in the framework of threshold models. However, since the existing models do not take into account individuals' optimization problem, it remains an open question what dynamics emerge in the diffusion process when individuals face multiple (and possibly incompatible) information. Here, we develop a microfounded general threshold model that enables us to analyze the collective dynamics of individual behavior in the propagation of multiple information. The analysis reveals that the virality of competing information is fundamentally indeterminate. When individuals maximize coordination with neighbors, the diffusion process is described as a saddle path, thereby leading to an unpredictable symmetry breaking. When individuals' choices are irreversible, there is a continuum of stable equilibria where a certain degree of social polarization takes place by chance.
