Identifying the starting point of a spreading process in complex networks

TL;DR

This paper presents a method to identify the initial source of a spreading process in complex networks by analyzing node centrality measures, validated on theoretical models and a real email network.

Contribution

It introduces a centrality-based approach for source detection in spreading processes, validated across multiple network types.

Findings

Source nodes tend to have highest centrality measures.

Method effective on both theoretical and real-world networks.

Centrality metrics can reliably identify the origin of spreading processes.

Abstract

When dealing with the dissemination of epidemics, one important question that can be asked is the location where the contamination began. In this paper, we analyze three spreading schemes and propose and validate an effective methodology for the identification of the source nodes. The method is based on the calculation of the centrality of the nodes on the sampled network, expressed here by degree, betweenness, closeness and eigenvector centrality. We show that the source node tends to have the highest measurement values. The potential of the methodology is illustrated with respect to three theoretical complex network models as well as a real-world network, the email network of the University Rovira i Virgili.