Influence minimization in linear threshold networks

The propagation of information and innovation in social networks has been widely studied in recent years. Most of the previous works focus on solving the problem of influence maximization, which aims to identify a small subset of early adopters in a social network to maximize the influence propagation under a given diffusion model. On the contrary in this paper, motivated by real-world scenarios, we propose two different influence minimization problems. We consider a linear threshold diffusion model and provide a general solution to the first problem by solving an integer linear programming problem. For the second problem, we provide a technique to search for an optimal solution that works only in particular cases and discuss a simple heuristic to find a solution in the general case. Several simulations on real datasets are also presented.