Multimedialne seminarium z ekono- i socjofizyki

The phenomena of spreading are essential part of social complex networks. Regardless of whether the virus, rumor or news is spread, very often the first question is where it comes from? In their seminal work, Pinto et al.[1] introduced gaussian maximum likelihood estimator for localization of single source, based on sparse observers placed in the network. During this lecture we will explore this method, learn its limitation and find out how to optimize it in terms of computing time[2] and precision[3].[1] Pinto, P. C., Thiran, P., & Vetterli, M. (2012). Locating the source of diffusion in large-scale networks. Physical Review Letters, 109(6), 1–5.[2] Paluch, R., Lu, X., Suchecki, K., Szymański, B. K., & Hołyst, J. A. (2018). Fast and accurate detection of spread source in large complex networks. Scientific Reports, 8(1), 2508.[3] Gajewski, Ł. G., Suchecki, K., & Hołyst, J. A. (2019). Multiple propagation paths enhance locating the source of diffusion in complex networks. Physica A, 519, 34–41.