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The dynamics of viral marketing
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Source Electronic Commerce archive
Proceedings of the 7th ACM conference on Electronic commerce table of contents
Ann Arbor, Michigan, USA
Pages: 228 - 237  
Year of Publication: 2006
ISBN:1-59593-236-4
Authors
Jure Leskovec  Carnegie Mellon University, Pittsburgh, PA
Lada A. Adamic  University of Michigan, Ann Arbor, MI
Bernardo A. Huberman  HP Labs, Palo Alto, CA
Sponsors
ACM: Association for Computing Machinery
SIGEcom: ACM Special Interest Group on Electronic Commerce
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 10,   Downloads (12 Months): 156,   Citation Count: 19
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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 then 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 product and pricing categories for which viral marketing seems to be very effective.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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D. Watts. A simple model of global cascades on random networks. PNAS, 99(9):4766--5771, Apr 2002.

CITED BY  19

Collaborative Colleagues:
Jure Leskovec: colleagues
Lada A. Adamic: colleagues
Bernardo A. Huberman: colleagues