2024/01/30 by James P. Gleeson, Gleeson, James P., Ailbhe Cassidy +5
Physics and Astronomy · #Complex Network Analysis Techniques #Data Analysis #FOS: Physical sciences #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph) #Statistics and Probability (physics.data-an)
paper · doi:10.48550/arxiv.2401.16978
openalex publication_date 2024/01/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
An algorithm for efficiently calculating the expected size of single-seed cascade dynamics on networks is proposed and tested. The expected size is a time-dependent quantity and so enables the identification of nodes who are the most influential early or late in the spreading process. The measure is accurate for both critical and subcritical dynamic regimes and so generalises the nonbacktracking centrality that was previously shown to successfully identify the most influential single spreaders in a model of critical epidemics on networks.