Identifying online opinion leaders using K-means clustering

Abstract

Online opinion leaders play an important role in the dissemination of information in discussion forums. They are a high-priority target group for viral marketing campaigns. On an average, an opinion leader will tell about his or her experience with a product or company to 14 other people. It is important to identify such opinion leaders from data derived from online activity of users. We present an approach to identification of opinion leaders using the K-means clustering algorithm. This approach does not require knowledge of the user's opinions or membership in other forums.