Minimizing the Misinformation in Social Networks using Heuristic Greedy Algorithm

Abstract

In recent years, online social media has grown in popularity, and a vast volume of information has circulated over social media platforms, altering people's access to information. The credibility of information material is being questioned, and various types of misinformation are using social media to propagate quickly. The importance of network space administration and maintaining a trusted network environment cannot be overstated. In this paper, we look at a new challenge termed the activity minimization of misinformation influence (AMMI) problem, which involves removing a group of nodes from the network in order to reduce the total amount of misinformation interaction between nodes (TAMIN). To put it another way, the AMMI challenge is to choose K nodes from a given social network G to block in order to minimize the TAMIN.We demonstrate that the objective function is neither submodular nor supermodular, and we suggest a heuristic greedy algorithm (HGA) for removing the top K nodes.