Online reputation systems have emerged as some of the most promising tools for fostering trust in online business and interpersonal interactions. These systems collect, aggregate, and distribute feedback about participants’ past behaviour. Although successfully used, current online reputation systems lack an important feature which is globality. Participants build a reputation within one community, and sometimes several reputations within several communities, but each reputation is bound to the corresponding community. Moreover, such reputation is usually computed using algorithms over which the inquiring agent has no control. This paper proposes one way of dealing with this problem. We introduce an online reputation centralizer that collects raw reputation data about users from several online communities and allows for it to be aggregated according to the inquiring agent’s requirements, using a stochastic trust model, and taking into account factors that qualify a user’s reputation.
Mendeley saves you time finding and organizing research
Choose a citation style from the tabs below