Fuzzy consensus model in collective knowledge systems: An application for fighting food frauds

Abstract

Food fraud is related to different illicit conducts which aim at gaining economic benefit from counterfeiting food and ignoring the damage they cause to public economy and health. Consumers use the new technologies, like social networks, in order to share their worries about food frauds and to stay informed about them. But, in such a complex and dynamic context, it is important to ensure the reliability of news about food frauds in order to avoid misinformation and general panic phenomena. In this context, we propose an extension of a Collective Knowledge System aiming at verifying the reliability of news about food frauds and to decide whether to publish and spread information on the food frauds in the society. A Fuzzy Consensus Model has been proposed for helping the experts in achieving a shared decision about the reliability of each news and about its publication and diffusion. An illustrative example demonstrates the feasibility and the usefulness of the proposed approach.