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Effects of Sampling in Spreading Processes

Grant number: 15/23587-2
Support Opportunities:Scholarships abroad - Research Internship - Master's degree
Effective date (Start): January 11, 2016
Effective date (End): July 10, 2016
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:Francisco Aparecido Rodrigues
Grantee:Bianca Madoka Shimizu Oe
Supervisor: Yamir Moreno Vega
Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Research place: Universidad de Zaragoza, Spain  
Associated to the scholarship:14/12301-8 - Statistical inference in complex networks, BP.MS

Abstract

Spreading processes, such as rumor and epidemic spreading, can be naturally seen as dynamic processes in complex networks. Individuals are represented by vertices and their relationship is represented by edges of a network. However, social networks can be too large to measure or even have an unknown size, making it hard to obtain a complete picture of them. Consequently, there are cases when sampled networks must be used instead of the real one. In this project, we intend to compare sampling techniques in order to learn which method is the best when dealing with spreading processes.

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