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Cited by 2,032

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

The dynamics of viral marketing

Open access
Leskovec, Jure, Adamic, Lada A., Huberman, Bernardo A.·2007·ACM Transactions on the Web
DOI 10.1145/1232722.1232727
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Abstract

We 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.

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Crossref · 10.1145/1232722.1232727

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Metadata

Authors
Leskovec, J., Adamic, L. A., & Huberman, B. A.
Venue
ACM Transactions on the Web
Publisher
Association for Computing Machinery (ACM)
Published
2007-05
Volume
1
Issue
1
Pages
5
ISSN
  • 1559-1131 (ISSN-L)
  • 1559-114X
DOI
10.1145/1232722.1232727
OpenAlex
W1994473607
Cited by
2,032
References
4
FWCI
39.52
Type
journal article
Language
en
Open access
green

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.