presented by Lada Adamic
Assistant Professor, School of Information
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 observed the propagation of recommendations and the cascade sizes, which can be explained by a stochastic model. We then established 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, there are product and pricing categories for which viral marketing seems to be very effective.
This is joint work with Jure Leskovec from CMU and Bernardo Huberman from HP Labs.
About the Speaker:
Lada A. Adamic is an assistant professor in the School of Information. Her research interests center on information dynamics in networks: how information diffuses, how it can be found, and how it influences the evolution of a network's structure. She worked previously in Hewlett-Packard's Information Dynamics Lab on research projects relating to networks constructed from large data sets. These projects included mining the medical literature for gene-disease connections, tracking and modeling information flow in E-mail and blog networks, modeling search processes on real-world social networks, and building expertise-finding systems.
Added by kinetisonic on October 28, 2005