We offer a proof system and a NetLogo simulation for trust and distrust in networks where contradictory information is shared by ranked lazy and sceptic agents. Trust and its negative are defined as properties of edges: the former is required when a message is passed bottom-up in the hierarchy or received by a sceptic agent; the latter is attributed to channels that require contradiction resolution, or whose terminal is a lazy agent. These procedures are associated with epistemic costs, respectively for confirmation and refutation. We describe the logic, illustrate the algorithms implemented in the model and then focus on experimental results concerning the analysis of epistemic costs, the role of the agents’ epistemic attitude on distrust distribution and the influence of (dis)trust in reaching consensus
