Network hubs cease to be influential in the presence of low levels of advertising

Attempts to find central "influencers," "opinion leaders," "hubs," "optimal seeds," or other important people who can hasten or slow diffusion or social contagion has long been a major research question in network science. We demonstrate that opinion leadershi...

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Bibliographic Details
Published inProceedings of the National Academy of Sciences - PNAS Vol. 118; no. 7
Main Authors Rossman, Gabriel, Fisher, Jacob C
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 16.02.2021
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Summary:Attempts to find central "influencers," "opinion leaders," "hubs," "optimal seeds," or other important people who can hasten or slow diffusion or social contagion has long been a major research question in network science. We demonstrate that opinion leadership occurs only under conventional but implausible scope conditions. We demonstrate that a highly central node is a more effective seed for diffusion than a random node if nodes can only learn via the network. However, actors are also subject to external influences such as mass media and advertising. We find that diffusion is noticeably faster when it begins with a high centrality node, but that this advantage only occurs in the region of parameter space where external influence is constrained to zero and collapses catastrophically even at minimal levels of external influence. Importantly, nearly all prior agent-based research on choosing a seed or seeds implicitly occurs in the network influence only region of parameter space. We demonstrate this effect using preferential attachment, small world, and several empirical networks. These networks vary in how large the baseline opinion leadership effect is, but in all of them it collapses with the introduction of external influence. This implies that, in marketing and public health, advertising broadly may be underrated as a strategy for promoting network-based diffusion.
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Author contributions: G.R. and J.C.F. designed research; performed research; analyzed data; and wrote the paper.
Edited by Paul DiMaggio, New York University, New York, NY, and accepted by Editorial Board Member Adrian E. Raftery January 7, 2021 (received for review June 30, 2020)
See online for related content such as Commentaries.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.2013391118