Abstract :

In recent times, the proliferation of online social media has transformed the information landscape, altering the dynamics of information access for individuals. This surge, however, has also ushered in challenges, particularly in the veracity of information, as various forms of misinformation proliferate rapidly through these social platforms. Ensuring effective governance of the online space and establishing a trusted network environment have become imperatives. This article delves into a novel problem termed the "Activity Minimization of Misinformation Influence" (AMMI) problem, aiming to identify a set of nodes in a network that, when blocked, minimizes the total amount of misinformation interaction between nodes (TAMIN). In essence, the AMMI problem seeks to strategically select K nodes within a given social network G to mitigate the overall TAMIN. We establish that the objective function lacks both submodular and supermodular properties and introduce a heuristic greedy algorithm