Abstract

With the tremendous popularity of social networking sites in this era of Web 2.0, increasingly more users are contributing their comments and opinions about products, people, organizations, and many other entities. These online comments often have direct influence on consumers’ buying decisions and the public’s impressions of enterprises. As a result, enterprises have begun to explore the feasibility of using social networking sites as platforms to conduct targeted marking and enterprise reputation management for e-commerce and e-business. As indicated from recent marketing research, the joint influence power of a small group of active users could have considerable impact on a large number of consumers’ buying decisions and the public’s perception of the enterprises. To help enterprises conduct cost-effective targeted marketing and reputation management, this paper illustrates a novel methodology that can effectively discover the most influential users from social networking sites (SNS). In particular, the general methodology of mining the influence network from SNS and the computational models of mathematical programming for discovering the user groups with the maximal joint influence power are proposed. The empirical evaluation with real data extracted from social networking sites shows that the proposed method can effectively identify the most influential groups when compared to the benchmark methods. This study opens the door to effectively conducting targeted marketing and enterprise reputation management on social networking sites.

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An Effective Method of Discovering Target Groups on Social Networking Sites

With the tremendous popularity of social networking sites in this era of Web 2.0, increasingly more users are contributing their comments and opinions about products, people, organizations, and many other entities. These online comments often have direct influence on consumers’ buying decisions and the public’s impressions of enterprises. As a result, enterprises have begun to explore the feasibility of using social networking sites as platforms to conduct targeted marking and enterprise reputation management for e-commerce and e-business. As indicated from recent marketing research, the joint influence power of a small group of active users could have considerable impact on a large number of consumers’ buying decisions and the public’s perception of the enterprises. To help enterprises conduct cost-effective targeted marketing and reputation management, this paper illustrates a novel methodology that can effectively discover the most influential users from social networking sites (SNS). In particular, the general methodology of mining the influence network from SNS and the computational models of mathematical programming for discovering the user groups with the maximal joint influence power are proposed. The empirical evaluation with real data extracted from social networking sites shows that the proposed method can effectively identify the most influential groups when compared to the benchmark methods. This study opens the door to effectively conducting targeted marketing and enterprise reputation management on social networking sites.