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. We test the threshold hypothesis of social influence with a large dataset of information diffusion on social media. 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. The practice of viral marketing needs innovative strategies to increase information novelty and reduce the excessive network threshold. In all, this research extends threshold models of social influence and underlines the nonlinear nature of social influence in information diffusion.
Cheng-Jun Wang, Jonathan J.H. Zhu
Publication date: 18 February 2021 Reprints & Permissions
Social influence plays a key role in determining the size of information diffusion. We test this hypothesis using a large dataset of information diffusion on social media. It finds that large network threshold, limited diffusion depth, and strong bursts become the bottlenecks that constrain online information diffusion.
Cheng-Jun Wang was supported by the Major Project of the National Social Science Fund of China (19ZDA324), the National Social Science Foundation of Jiangsu Province (19JD001), and the Fundamental Research Funds for the Central Universities (011014370119). Jonathan Zhu was supported in part by GRF11505119 from Hong Kong SAR Research Grants Council and HKIDS9360163 from City University of Hong Kong.
Wang, C.-J. and Zhu, J.J.H. (2021), Jumping over the network threshold of information diffusion: testing the threshold hypothesis of social influence, Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-08-2019-0313