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The Dynamics of Viral Marketing JURE LESKOVEC Carnegie Mellon University (2008)

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.

Publication details
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.94.3792
Source http://labs.rightnow.com/colloquium/papers/viral.pdf
Contributors CiteSeerX
Repository CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Keywords Categories and Subject Descriptors, J.4 [Social and Behavioral Sciences, Economics General Terms, Economics Additional Key Words and Phrases, E-commerce, Long tail, Recommender systems, Viral marketing
Type text
Language English
Relation 10.1.1.1.9196, 10.1.1.129.6877, 10.1.1.19.7697, 10.1.1.133.1588, 10.1.1.140.8751