document: Mining the network value of customers One of the major applications of data mining is in helping companies determine which potential customers to market to . If the expected profit from a customer is greater than the cost of marketing to her , the marketing action for that customer is executed . So far , work in this area has considered only the intrinsic value of the customer ( i. e , the expected profit from sales to her ) . We propose to model also the customer 's network value : the expected profit from sales to other customers she may influence to buy , the customers those may influence , and so on recursively . Instead of viewing a market as a set of independent entities , we view it as a social network and model it as a Markov random field . We show the advantages of this approach using a social network mined from a collaborative filtering database . Marketing that exploits the network value of customers -- also known as viral marketing -- can be extremely effective , but is still a black art . Our work can be viewed as a step towards providing a more solid foundation for it , taking advantage of the availability of large relevant databases .
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