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

Cheng-Jun Wang (School of Journalism and Communication, Nanjing University, Nanjing, China)
Jonathan J.H. Zhu (Department of Media and Communication, City University of Hong Kong, Kowloon Tong, Hong Kong) (Web Mining Lab, Department of Media and Communication, City University of Hong Kong, Kowloon Tong, Hong Kong)

Internet Research

ISSN: 1066-2243

Article publication date: 18 February 2021

Issue publication date: 1 November 2021

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Abstract

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.

Keywords

Acknowledgements

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.

Citation

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. 31 No. 5, pp. 1677-1694. https://doi.org/10.1108/INTR-08-2019-0313

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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