Jumping over the network threshold of information diffusion: testing the threshold hypothesis of social influence
利用社交媒体上的大规模数据集，检验了社会影响与信息扩散规模之间的非线性关系，发现存在倒U形关系，且网络阈值、扩散深度和爆发强度是限制扩散规模的关键因素。
Purpose Social influence plays a crucial role in determining the size of information diffusion. Drawing on threshold models, we reformulate the nonlinear threshold hypothesis of social influence. Design/methodology/approach We test the threshold hypothesis of social influence with a large dataset of information diffusion on social media. Findings There exists a bell-shaped relationship between social influence and diffusion size. However, the large network threshold, limited diffusion depth and intense bursts become the bottlenecks that constrain the diffusion size. Practical implications The practice of viral marketing needs innovative strategies to increase information novelty and reduce the excessive network threshold. Originality/value In all, this research extends threshold models of social influence and underlines the nonlinear nature of social influence in information diffusion.