Energy saving information cascades in online social networks: An agent-based simulation study

Qi Wang, John E. Taylor

Abstract: Information shared through online social networking platforms is spread from user to user. Although some researchers have argued that this phenomenon can unfold similarly to an epidemic, others have found that information disseminates within a narrow range, propagating only a few levels in a communication network. In an effort to resolve these conflicting findings, we developed an information cascade model to conduct a variance-based global sensitivity analysis (GSA) to determine the influence of two network attributes on the diffusion of energy saving information. The simulation results of the base model showed that energy saving information failed to generate deep cascades. Also, the results from the GSA demonstrated that network density and the number of an initiator's connections had limited influence on information cascades. These findings suggest that massive network structures and a large number of potential recipients do not engender deep cascades of energy saving information in online social networks.