The Dynamics of Viral Marketing

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dc.creatorLeskovec, Jure
dc.creatorAdamic, Lada A.
dc.creatorHuberman, Bernardo A.
dc.date2005-09-05
dc.date2007-04-20
dc.date.accessioned2026-07-07T07:57:26Z
dc.date.available2026-07-07T07:57:26Z
dc.descriptionWe present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a million products. We observe the propagation of recommendations and the cascade sizes, which we explain by a simple stochastic model. We analyze how user behavior varies within user communities defined by a recommendation network. Product purchases follow a 'long tail' where a significant share of purchases belongs to rarely sold items. We establish how the recommendation network grows over time and how effective it is from the viewpoint of the sender and receiver of the recommendations. While on average recommendations are not very effective at inducing purchases and do not spread very far, we present a model that successfully identifies communities, product and pricing categories for which viral marketing seems to be very effective.
dc.identifierhttps://arxiv.org/abs/physics/0509039
dc.identifierhttp://arxiv.org/abs/physics/0509039
dc.identifierLeskovec, J., Adamic, L. A., and Huberman, B. A. 2007. The dynamics of viral marketing. ACM Transactions on the Web, 1, 1 (May 2007)
dc.identifierdoi:10.1145/1232722.1232727
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/127648
dc.subjectPhysics and Society
dc.subjectStatistical Mechanics
dc.subjectDatabases
dc.subjectData Structures and Algorithms
dc.titleThe Dynamics of Viral Marketing
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