Richardson and Domingos KDD 2002

Citation

 author = {Richardson, Matthew and Domingos, Pedro},
 title = {Mining knowledge-sharing sites for viral marketing},
 booktitle = {Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining},
 series = {KDD '02},
 year = {2002},
 isbn = {1-58113-567-X},
 location = {Edmonton, Alberta, Canada},
 pages = {61--70},
 numpages = {10},
 url = {http://doi.acm.org/10.1145/775047.775057},

Abstract from the paper

Viral marketing takes advantage of networks of influence among customers to inexpensively achieve large changes in behavior. Our research seeks to put it on a firmer footing by mining these networks from data, building probabilistic models of them, and using these models to choose the best viral marketing plan. Knowledge-sharing sites, where customers review products and advise each other, are a fertile source for this type of data mining. In this paper we extend our previous techniques, achieving a large reduction in computational cost, and apply them to data from a knowledge-sharing site. We optimize the amount of marketing funds spent on each customer, rather than just making a binary decision on whether to market to him. We take into account the fact that knowledge of the network is partial, and that gathering that knowledge can itself have a cost. Our results show the robustness and utility of our approach.