Blocking the Spread of Misinformation in a Network under Distinct Cost Models

Fernando C. Erd, André Luís Vignatti, Murilo V. G. da Silva

Abstract: Given a network N and a set of nodes that are the starting point for the spread of misinformation across N and an integer k, in the influence blocking maximization problem the goal is to find k nodes in N as the starting point for a competing information (say, a correct information) across N such that the reach of the misinformation is minimized. In this paper we deal with a more realistic scenario for this problem where different nodes have different costs and the counter strategy has a “budget” for picking nodes for a solution. Our experimental results show that the success of a given strategy varies substantially depending on the cost function in the model. In particular, we investigate the cost function where all nodes have cost 1 and a cost function that assigns higher costs to higher degree nodes. We show that, even though strategies that perform well in these two diverse cases are very different from each other, both correlate well with simple (but different) strategies: greedily choose high degree nodes and choose nodes uniformly at random.