On Countering Disinformation with Caution: Effective Inoculation Strategies and Others that Backfire into Community Hyper-Polarization

Abstract

The increasing adoption of social media platforms as a means of communication has made them into one of the main targets for disinformation and misinformation campaigns due, in part, to the speed increase and cost decrease of communication provided by these platforms. Given that facts and opinions are proposed, discussed and adopted by users of these platforms, countering this threat needs a better understanding of the dynamics by which false and misleading information spreads and gets adopted by users. This work develops an agent-based model that simulates an organized disinformation campaign performed by a group of users referred to as conspirators, which are opposed by a parallel organization acting as a barrier to the spread of disinformation, the inoculators. The exploration of the simulation results shows how different macroscopic states in respect to a disinformation infection and the stages for a macroscopic consensus exist. The control of the simulation based upon the model parameters allows the progression of the complete network to converge and separate over time. This provides insight into a plausible feature of social networks where the macrostate of the system depends upon the parameter values and can be modified. The relationship between these values is explored and provides intuition into aspects of a community which are necessary to withstand disinformation campaigns. The results also provide an important cautionary note that after a certain degree of conspiracy counter measures a network may become hyper-polarized.