2020/12/03 by Robert Paluch, Łukasz G. Gajewski, Paluch, Robert +5
Computer Science · Physics and Astronomy · #Computers and Society (cs.CY) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Social and Information Networks (cs.SI) #Statistics and Probability (physics.data-an) #cs.CY #cs.SI #physics.data-an
paper · pdf · doi:10.48550/arxiv.2012.02023
11 pages, 8 figures
arxiv created 2020/12/03 · arxiv updated 2020/12/04
Nowadays it is not uncommon to have to deal with dissemination on multi-layered networks and often finding the source of said propagation can be a crucial task. In this paper we tackle this exact problem with a maximum likelihood approach that we extend to be operational on multi-layered graphs. We test our method for source location estimation on synthetic networks and outline its potential strengths and limitations. We also observe some non-trivial and perhaps surprising phenomena where the more of the system one observes the worse the results become whereas increased problem complexity in the form of more layers can actually improve our performance.