Identifying valuable customers on social networking sites for profit maximization

Authors:
Kaiquan Xu;Jiexun Li;Yuxia Song
Affiliations:
School of Business, Nanjing University, Nanjing 210093, China;College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, United States;Department of Information Engineering, Yingtian College, Nanjing 210046, China
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

With the tremendous popularity of social networking sites (SNS) in this era of Web 2.0, enterprises have begun to explore the feasibility of using SNS as platforms to conduct targeted marking and reputation management. Given huge number of users on SNS, how to choose appropriate users as the targets is the key for enterprises to conduct cost-effective targeted marketing and reputation management on SNS. This paper introduces a novel model for effectively identifying the most valuable users from SNS. Furthermore, we propose to use an optimization technique named semidefinite programming (SDP) to identify the most valuable customers that can generate the maximum of total profit. Our empirical evaluation on a real data set extracted from a popular SNS shows that the proposed model achieves much higher profits than benchmark methods. This study opens doors to more effective targeted marketing and reputation management on SNS.