Preventing Epidemic by Social Network Analysis Defining New Metrics

In this paper, we aim to find a method for preventing epidemics by using social network analysis and finding the persons who have main role in spreading an imaginary illness. Authors study the specification of a network for illness spreading in a real network of students that they physically contact each other in different places via handshaking or kissing. After doing analysis, a set of nodes with higher centralities are deleted from network and is compared with randomly selected group. During designed procedure, a new overhead metric for examining network illness influence is suggested and its importance is discussed. This study searches to find the best group of nodes for limiting the epidemic. The results show that our proposed metrics can more efficiently interpret and optimize the previous studies.

Keywords:

Epidemic , Social Networks , Network Centrality , Information Diffusion