Modeling the Influence of Fake Accounts on User Behavior and Information Diffusion in Online Social Networks

The mechanisms of information diffusion in Online Social Networks (OSNs) have been studied extensively from various perspectives with some focus on identifying and modeling the role heterogeneous nodes. However, none these studies considered influence fake accounts human how this will affect rumor process. This paper aims to present a new model that characterizes bots process OSNs. proposed SIhIbR extends classical SIR by introducing two types infected users different infection rates: who are (Ih) normal rate bot (Ib) reflects intent steadiness type account spread rumors. has measured using social impact theory, as it better deliberate behavior large portion network considering both strength bias source node. experiment results show accuracy outperforms when simulating existence accounts. It concluded accelerate they many people short time.