Jumping over the network threshold of information diffusion : testing the threshold hypothesis of social influence

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

6 Scopus Citations
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Original languageEnglish
Pages (from-to)1677-1694
Journal / PublicationInternet Research
Issue number5
Online published18 Feb 2021
Publication statusPublished - 1 Nov 2021


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.

Research Area(s)

  • Information diffusion, Information modeling, Social influence, Social networks, Threshold models