Effectual Seed Pick Framework Focusing on Maximizing Influence in Social Networks

Abstract

Today, the emergence of social media is helpful for the healthcare system where everyone is closely connected. Large numbers of people can be reached by using seed nodes to provide medical advice, facilities, new changes in the treatment, and any health ministry guidelines. As today’s world is dealing with COVID-19, the main objective is to provide healthcare services to many people irrespective of time and locality. As people suffering from corona are dealing with mental health issues, in order to deal with it, a seed pick framework using machine learning for the influence maximization technique is proposed, which will be helpful to provide pervasive healthcare. For pervasive healthcare, an effectual seed pick framework is required focusing on influence maximization using machine learning. The proposed algorithm Fuzzy-VIKOR is helpful to identify the targeted node to spread information at a high rate. Consequently, the proposed structure effectively addresses different issues related to a large number of patients, and thus, increased influence maximization using seed nodes is helpful for pervasive healthcare. The experiments show that the proposed framework has high precision, accuracy, F1-score, and recall compared to other existing algorithms employed to find influence maximization seeds.