<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Jonathan J.H. Zhu | Cheng-Jun Wang</title><link>https://chengjun.github.io/authors/jonathan-j.h.-zhu/</link><atom:link href="https://chengjun.github.io/authors/jonathan-j.h.-zhu/index.xml" rel="self" type="application/rss+xml"/><description>Jonathan J.H. Zhu</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><copyright>Copyright © Cheng-Jun Wang 2026 Know Yourself</copyright><lastBuildDate>Thu, 18 Feb 2021 22:20:56 +0800</lastBuildDate><image><url>https://chengjun.github.io/media/icon_huee78856177679f3c0297a865dd42e38b_9502_512x512_fill_lanczos_center_3.png</url><title>Jonathan J.H. Zhu</title><link>https://chengjun.github.io/authors/jonathan-j.h.-zhu/</link></image><item><title>Jumping over the Network Threshold of Information Diffusion</title><link>https://chengjun.github.io/publication/weibo-threshold/</link><pubDate>Thu, 18 Feb 2021 22:20:56 +0800</pubDate><guid>https://chengjun.github.io/publication/weibo-threshold/</guid><description>&lt;p>
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&lt;h3 id="jumping-over-the-network-threshold-of-information-diffusion-testing-the-threshold-hypothesis-of-social-influence">Jumping over the network threshold of information diffusion: testing the threshold hypothesis of social influence&lt;/h3>
&lt;p>Cheng-Jun Wang, Jonathan J.H. Zhu&lt;/p>
&lt;p>&lt;strong>Internet Research&lt;/strong>&lt;/p>
&lt;p>ISSN: 1066-2243&lt;/p>
&lt;p>Publication date: 18 February 2021 Reprints &amp;amp; Permissions&lt;/p>
&lt;blockquote>
&lt;p>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.&lt;/p>
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&lt;h3 id="acknowledgements">Acknowledgements&lt;/h3>
&lt;p>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.&lt;/p>
&lt;h3 id="citation">Citation&lt;/h3>
&lt;p>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. &lt;a href="https://doi.org/10.1108/INTR-08-2019-0313" target="_blank" rel="noopener">https://doi.org/10.1108/INTR-08-2019-0313&lt;/a>&lt;/p></description></item><item><title>Jumping onto the Bandwagon of Collective Gatekeepers: Testing the Bandwagon Effect of Information Diffusion on Social News Website</title><link>https://chengjun.github.io/publication/bandwagon/</link><pubDate>Sun, 03 Mar 2019 22:20:56 +0800</pubDate><guid>https://chengjun.github.io/publication/bandwagon/</guid><description>&lt;p>
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&lt;p>&lt;strong>Jumping onto the Bandwagon of Collective Gatekeepers: Testing the Bandwagon Effect of Information Diffusion on Social News Website&lt;/strong>&lt;/p>
&lt;p>Cheng-Jun Wang $ ^{a,b}$ * , Jonathan J.H. Zhu ${^b}$&lt;/p>
&lt;p>$^a$ Computational Communication Collaboratory, School of Journalism and Communication, Nanjing University, Nanjing, China&lt;/p>
&lt;p>$^b$ Web Mining Lab, Department of Media and Communication, City University of Hong Kong, Hong Kong, China&lt;/p>
&lt;h2 id="keywords">Keywords&lt;/h2>
&lt;p>Information Diffusion; Collective Gatekeeping; Interpersonal Effects; Bandwagon Effects; Threshold Model&lt;/p>
&lt;p>The results demonstrate that the bandwagon of collective gatekeepers is the primary driver for online news diffusion. Interestingly, the bandwagon effect of collective gatekeeping is moderated by the strength of interpersonal effects. The theoretical generalizations of this research contribute to our understanding about the impact of collective gatekeeping on information diffusion.&lt;/p>
&lt;h2 id="highlights">Highlights&lt;/h2>
&lt;ol>
&lt;li>Drawing on threshold models to capture the interpersonal effects and collective gatekeeping, we test our hypothesis with two novel datasets of information diffusion on social media.&lt;/li>
&lt;li>The findings demonstrate that both bandwagon effect and interpersonal effect play important roles in collective gatekeeping on social media.&lt;/li>
&lt;li>The bandwagon of collective gatekeepers is the primary driver for online news diffusion&lt;/li>
&lt;li>The bandwagon effect of collective gatekeeping is moderated by the strength of interpersonal effects.&lt;/li>
&lt;/ol>
&lt;p>Telematics and Informatics&lt;/p>
&lt;ul>
&lt;li>Received at Editorial Office 2 Jul 2018&lt;/li>
&lt;li>Article 3rd revised 19 Feb 2019&lt;/li>
&lt;li>Article accepted for publication 3 Mar 2019&lt;/li>
&lt;/ul>
&lt;p>Please cite this article as:&lt;/p>
&lt;blockquote>
&lt;p>Wang, C-J. * , Zhu, J.J.H.(2019) Jumping onto the Bandwagon of Collective Gatekeepers: Testing the Bandwagon Effect of Information Diffusion on Social News Website, Telematics and Informatics. 41:34-45, doi: &lt;a href="https://doi.org/10.1016/j.tele.2019.03.001" target="_blank" rel="noopener">https://doi.org/10.1016/j.tele.2019.03.001&lt;/a>&lt;/p>
&lt;/blockquote></description></item><item><title>Discussing Occupy Wall Street on Twitter</title><link>https://chengjun.github.io/publication/dicuss-ows-tweets/</link><pubDate>Thu, 12 Sep 2013 00:00:00 +0000</pubDate><guid>https://chengjun.github.io/publication/dicuss-ows-tweets/</guid><description>&lt;p>More detail can easily be written here using &lt;em>Markdown&lt;/em> and $\rm \LaTeX$ math code.&lt;/p></description></item></channel></rss>