Hybrid WOM collection and visualization method for reputation rating in online community

Abstract

Recently, the websites involved in online transaction lacks explicit information on the reputation of the users acting as raters. This problem could be solved if there is a third party to guide the candidates involved in the online transaction. Online source of information about web documents need many users' evaluations. Such information can be available for other users. The feedback of the users can reorganize the group and refine the knowledge level that a group of human experts provide. We generate Word of Mouth (WOM) metrics and show the reputation as allegorical figuration by 3D graphic visualization. We found out possible WOM candidate and they can provoke the opinions.