| The dynamics of viral marketing |
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Electronic Commerce
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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
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Downloads (6 Weeks): 29, Downloads (12 Months): 167, 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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CITED BY 19
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Lars Backstrom , Dan Huttenlocher , Jon Kleinberg , Xiangyang Lan, Group formation in large social networks: membership, growth, and evolution, Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, August 20-23, 2006, Philadelphia, PA, USA
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Jure Leskovec , Andreas Krause , Carlos Guestrin , Christos Faloutsos , Jeanne VanBriesen , Natalie Glance, Cost-effective outbreak detection in networks, Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, August 12-15, 2007, San Jose, California, USA
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Esteban Arcaute , Adam Kirsch , Ravi Kumar , David Liben-Nowell , Sergei Vassilvitskii, On threshold behavior in query incentive networks, Proceedings of the 8th ACM conference on Electronic commerce, June 11-15, 2007, San Diego, California, USA
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Jon M. Kleinberg, Challenges in mining social network data: processes, privacy, and paradoxes, Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, p.4-5, August 12-15, 2007, San Jose, California, USA
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Tim Carnes , Chandrashekhar Nagarajan , Stefan M. Wild , Anke van Zuylen, Maximizing influence in a competitive social network: a follower's perspective, Proceedings of the ninth international conference on Electronic commerce, August 19-22, 2007, Minneapolis, MN, USA
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David Crandall , Dan Cosley , Daniel Huttenlocher , Jon Kleinberg , Siddharth Suri, Feedback effects between similarity and social influence in online communities, Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2008, Las Vegas, Nevada, USA
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Lei Guo , Enhua Tan , Songqing Chen , Xiaodong Zhang , Yihong (Eric) Zhao, Analyzing patterns of user content generation in online social networks, Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, June 28-July 01, 2009, Paris, France
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Masahiro Kimura , Kazumi Saito , Ryohei Nakano, Extracting influential nodes for information diffusion on a social network, Proceedings of the 22nd national conference on Artificial intelligence, p.1371-1376, July 22-26, 2007, Vancouver, British Columbia, Canada
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