Semi-Global Circular Centrality to find Influential Spreaders

Smartphone use and social network connectivity are becoming more popular. Information sharing is becoming easier and faster. Influential spreaders in social networks play an important role. The identification of these influential nodes becomes a critical issue in social network analysis. Centrality methods are used to identify the influential nodes. There are many centrality methods proposed by researchers. The centrality methods can be classified into mainly four types: local centrality method, global centrality method, semi-global centrality method, and hybrid centrality. However, we have observed that the semi-global centrality method is identifying the ranks of a node based on the few levels of connectivity of a node and has not taken so much time. We are now proposing a new node ranking method called the “semi-global circular method.” This method finds the top influential spreaders in the dense part of the network. We have applied the susceptible–infected–recovered epidemic model to our toy network to examine the performance of the proposed method. The result shows us that the performance of the proposed method is good.