{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T19:33:43Z","timestamp":1781206423744,"version":"3.54.1"},"reference-count":57,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2021,2,18]],"date-time":"2021-02-18T00:00:00Z","timestamp":1613606400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["INTR"],"published-print":{"date-parts":[[2021,11,1]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>We test the threshold hypothesis of social influence with a large dataset of information diffusion on social media.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title><jats:p>The practice of viral marketing needs innovative strategies to increase information novelty and reduce the excessive network threshold.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>In all, this research extends threshold models of social influence and underlines the nonlinear nature of social influence in information diffusion.<\/jats:p><\/jats:sec>","DOI":"10.1108\/intr-08-2019-0313","type":"journal-article","created":{"date-parts":[[2021,2,18]],"date-time":"2021-02-18T13:41:22Z","timestamp":1613655682000},"page":"1677-1694","source":"Crossref","is-referenced-by-count":11,"title":["Jumping over the network threshold of information diffusion: testing the threshold hypothesis of social influence"],"prefix":"10.1108","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9507-2888","authenticated-orcid":false,"given":"Cheng-Jun","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6173-6941","authenticated-orcid":false,"given":"Jonathan J.H.","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2021,2,18]]},"reference":[{"key":"key2022092213504515300_ref001","first-page":"2329","article-title":"Diffusion of innovations in social networks","year":"2011"},{"issue":"9","key":"key2022092213504515300_ref002","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1287\/mnsc.1110.1421","article-title":"Creating social contagion through viral product design: a randomized trial of peer influence in networks","volume":"57","year":"2011","journal-title":"Management Science"},{"issue":"51","key":"key2022092213504515300_ref003","doi-asserted-by":"crossref","first-page":"21544","DOI":"10.1073\/pnas.0908800106","article-title":"Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks","volume":"106","year":"2009","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"key2022092213504515300_ref004","first-page":"434","article-title":"Trends in social media: persistence and decay","year":"2011"},{"key":"key2022092213504515300_ref005","first-page":"65","article-title":"Everyone's an influencer: quantifying influence on Twitter","year":"2011"},{"key":"key2022092213504515300_ref006","first-page":"519","article-title":"The role of social networks in information diffusion","year":"2012"},{"issue":"10","key":"key2022092213504515300_ref007","article-title":"Cumulative effect in information diffusion: empirical study on a microblogging network","volume":"8","year":"2013","journal-title":"PloS One"},{"issue":"1","key":"key2022092213504515300_ref008","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1093\/comnet\/cnt006","article-title":"Cascading behaviour in complex socio-technical networks","volume":"1","year":"2013","journal-title":"Journal of Complex Networks"},{"key":"key2022092213504515300_ref009","volume-title":"Structural Holes: The Social Structure of Competition","year":"1992"},{"key":"key2022092213504515300_ref010","unstructured":"Cao, Z. 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