You reap where you sow: a trust-based approach to initial seeding for viral advertising

Jisu Huh, Hyejin Kim, Bhavtosh Rath, Xinyu Lu, Jaideep Srivastava

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


This study examines the role of source trust in viral ad diffusion, specifically the impact of source trust on the reach and speed of ad diffusion. It tests the feasibility of using computer-algorithm-generated social media metrics, indicating the degree to which each person is trusted by others within a social network, for trust-based viral ad seeding strategy, and future research on viral advertising. Applying trust theory and the computational trust research approach using real-life viral ad cases, this study found that only a small proportion of social media users exposed to viral ads tend to contribute to ad diffusion, and those with higher trust scores make significantly stronger contributions to spreading viral ads faster and more broadly. Additionally, individuals’ source trust scores have stronger impact on the extent and speed of viral ad diffusion, especially in the situation where the ads contained socially-controversial messages. Theoretical and methodological contributions and practical implications are offered.

Original languageEnglish (US)
Pages (from-to)963-989
Number of pages27
JournalInternational Journal of Advertising
Issue number7
StatePublished - Oct 2020

Bibliographical note

Publisher Copyright:
© 2020 Advertising Association.


  • Viral advertising
  • computational research
  • computational trust
  • social media advertising
  • trust


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