Image and Reputation Coping Differently with Massive Informational Cheating

  • Authors:
  • Walter Quattrociocchi;Mario Paolucci;Rosaria Conte

  • Affiliations:
  • Laboratory of Agent Based Social Simulation - Institute of Cognitive Sciences and Technologies - CNR Rome, Italy;Laboratory of Agent Based Social Simulation - Institute of Cognitive Sciences and Technologies - CNR Rome, Italy;Laboratory of Agent Based Social Simulation - Institute of Cognitive Sciences and Technologies - CNR Rome, Italy

  • Venue:
  • WSKS '09 Proceedings of the 2nd World Summit on the Knowledge Society: Visioning and Engineering the Knowledge Society. A Web Science Perspective
  • Year:
  • 2009

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Abstract

Multi-agent based simulation is an arising scientific trend which is naturally provided of instruments able to cope with complex systems, in particular the socio-cognitive complex systems. In this paper, a simulation-based exploration of the effect of false information on social evaluation formation is presented. We perform simulative experiments on the RepAge platform, a computational system allowing agents to communicate and acquire both direct (image) and indirect and unchecked (reputation) information. Informational cheating, when the number of liars becomes substantial, is shown to seriously affect quality achievement obtained through reputation. In the paper, after a brief introduction of the theoretical background, the hypotheses and the market scenario are presented and the simulation results are discussed with respect to the agents' decision making process, focusing on uncertainty, false information spreading and quality of contracts.