When the influencer says jump! How influencer signaling affects engagement with COVID-19 misinformation

https://doi.org/10.1016/j.socscimed.2022.115497Get rights and content

Highlights

  • SMI-promotion elicited more social media engagement and credibility.

  • SMI-promotion also increased purchase likelihood.

  • Authentic information elicited the most SME, credibility, and purchase likelihood.

  • The detail of the information also played a role.

  • A multi-signal messaging approach with SMI promotion is most effective.

Abstract

With signaling theory, credibility, and social media engagement (SME) as guiding frameworks, this study used an experiment to examine how social media influencers (SMIs) affect how people engage with COVID-19 misinformation. SMI-promoted information elicited more SME, credibility, and purchase likelihood than non-SMI promoted information. The most effective message was a post promoted by an SMI that contained detailed information about an authentic product. However, data indicated nuance regarding the effect of SMIs. The authenticity of the information as well as the amount of detail in the post played a role. Additionally, mediated effects analysis showed that the impact of SME on purchase likelihood was higher among non-SMI followers. Data suggests that using a multi-signal messaging approach is suitable regardless of promotion by an SMI. This has important implications to public health messaging and the author discusses how health agencies may effectively signal information to the public.

Keywords

Signaling
Credibility
Social media influencers
Misinformation
Structural equation modeling
COVID-19

Data availability

Data will be made available on request.

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Ben Wasike is a professor in the Communication Department at the University of Texas Rio Grande Valley. He teaches classes in visual communication, communication theory, and research methods, among others. His research focuses on social media communication, political communication, visual communication, and law and policy issues.

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