To live or to die: Encountering conflict information dissemination over simple networks

Abstract

In an era of networks in which any individual is connected with one another, such as Internet of Things (IoT) and Online Social Networks (OSNs), the networks are evolving into complex systems, carrying a huge volume of information that may provoke even more. An interesting, yet challenging question is how such information dissemination evolves, that is, to continue or to stop. Specifically, we aim to find out the aftermath of epidemic spreading via individuals and conflicting information dissemination. From a holistic, networking view, it is impossible to take every aspect into accounts for complex networks toward these questions. Therefore, we establish a Susceptible-Infectious-Cured (SIC) propagation model to examine two simple network topologies, clique and star, in terms of extinction time and half-life time of information under controllable, epidemic dynamics. For a network of size n, both theoretical and numerical results suggest that extinction time and half-life time are O(log n/n) for clique networks, and O(log n) for star networks. More interestingly, given an initial network state I0, the extinction time is constant (O(1)) for cliques, and O(log I0) for stars; while the half-life time is O(log 1/I0) for both clique and star networks, respectively. In addition, we developed a method to estimate the conditional infection count distribution, which indicates the scope of information dissemination.