Multiple propagation paths enhance locating the source of diffusion in complex networks
| Autor: | Łukasz G. Gajewski, Janusz A. Hołyst, Krzysztof Suchecki |
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| Rok vydání: | 2019 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Statistics and Probability Physics - Physics and Society Computer science FOS: Physical sciences Computer Science - Social and Information Networks Physics and Society (physics.soc-ph) Complex network Condensed Matter Physics 01 natural sciences 010305 fluids & plasmas Vertex (geometry) 0103 physical sciences Shortest path problem Diffusion (business) 010306 general physics Algorithm |
| Zdroj: | Physica A: Statistical Mechanics and its Applications |
| ISSN: | 0378-4371 |
| DOI: | 10.1016/j.physa.2018.12.012 |
| Popis: | We investigate the problem of locating the source of diffusion in complex networks without complete knowledge of nodes’ states. Some currently known methods assume the information travels via a single, shortest path, which by assumption is the fastest way. We show that such a method leads to the overestimation of propagation time for synthetic and real networks, where multiple shortest paths as well as longer paths between vertices exist. We propose a new method of source estimation based on maximum likelihood principle, that takes into account existence multiple shortest paths. It shows up to 1.6 times higher accuracy in synthetic and real networks. |
| Databáze: | OpenAIRE |
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