Collaboration and Human Factor as Drivers for Reputation System Effectiveness

Abstract

Reputation management is about evaluating an agent’s actions and other agents’ opinions about those actions, reporting on those actions and opinions, and reacting to that report thus creating a feedback loop. This social mechanism has been successfully used, through Reputation Management Systems (RMSs) to classify agents within normative systems. Most RMSs rely on the feedbacks given by the member of the social network in which the RMS itself operates. In this way, the reputation index can be seen as an endogenous and self produced indicator, created by the users for the users’ benefit. This implies that users’ participation and collaboration is a key factor for the effectiveness a RMS. In this work the above factor is explored by means of an agent based simulation, and is tested on a P2P network for file sharing.