Profiling participants in online-community based on influence diffusion model

Text-based communication in an online-community obscures the characteristics of the participants that aid social interaction. In this paper, we propose a new method for profiling participants in an online-community to help the participants gain a better grasp of their social milieu, i.e., who are the other participant, what are their characteristics, and what are their roles. The proposed algorithm is based on Influence Diffusion Model (IDM), a method for discovering influential comments, opinion leaders, and interesting terms from threaded online discussions. We applied the proposed algorithm to eight electronic message boards, and confirmed higher precision and coverage values than other traditional keyword-based profiling methods.