Analysis Spreading Patterns Generated by Model
| Autor: | Alexandre G. Evsukoff, Carolina Ribeiro Xavier, Thiago Schons, Vinícius da Fonseca Vieira, Nelson F. F. Ebecken |
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| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
03 medical and health sciences Range (mathematics) 030104 developmental biology Diffusion process Computer science 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 02 engineering and technology Statistical physics Diffusion (business) |
| Zdroj: | Computational Science and Its Applications – ICCSA 2016 ISBN: 9783319420912 ICCSA (5) |
| DOI: | 10.1007/978-3-319-42092-9_26 |
| Popis: | Spreading have been studied in networks from a wide range of contexts, such as social, biological and technological. Models for spreading simulation can be applied to real world networks in order to investigate how spreading phenomena occurs from different perspectives. An usual approach is to analyst a diffusion process by assessing the number of reached nodes and the depth of a propagation. This work describes the spreading processes by identifying their patterns, characterized by the canonical name of the propagation trees started by each seeder. Diffusion was investigated in four real world networks considering Independent Cascade Model (ICM). The results show that, as observed in real world scenarios, the occurrence of complex cascades is quite rare and the majority of propagation trees are very simple. |
| Databáze: | OpenAIRE |
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