Abstract
Online forums have been extensively used in many knowledge management practices as well as online communities for sharing knowledge. Identifying who are experts of certain topics is essential to effective knowledge sharing in online forums. Existing expert identification techniques can broadly be classified into two major categories: content-based and communication-based expert identification techniques. However, they incur several limitations when applying to expert identification from online forums. In this study, we propose an expert identification technique on the basis of opinion ratings by members in online forums. Specifically, we extend PageRank, a graph-based ranking mechanism commonly employed by existing communication-based expert identification techniques and propose an ExpertRank algorithm that considers both positive and negative opinion ratings in communications in online forums. Using three datasets collected from a product review website (ie.., Epinions.com), our empirical evaluation results show that our proposed ExpertRank algorithm outperforms PageRank.