An Effective Method of Discovering Target Groups on Social Networking Sites

With the popularity of social networking sites (SNS) in this era of Web 2.0, increasingly more users are contributing their opinions about products and organizations. 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 use SNS to conduct targeted marking and reputation management. As indicated from recent marketing research, the joint influence power of a small group of active users could have considerable impact on 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 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 SNS 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 SNS.