Information Diffusion on the Iterated Local Transitivity Model of Online Social Networks
Understanding how information and rumors spread is a key issue for modern society. Malicious or inaccurate rumors can lead to unnecessary panic and generate social and economic instability. The authors study a recently introduced deterministic model of competitive information diffusion on the Iterated Local Transitivity (ILT) model of Online Social Networks (OSNs). In particular, they show that, for 2 competing agents, an in-dependent Nash Equilibrium (N.E.) on the initial graph remains a N.E. for all subsequent times. They also describe an example showing that this conclusion does not hold for general N.E. in the ILT process.