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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Influence maximization by rumor spreading on correlated networks through community identification

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Author(s):
Vega-Oliveros, Didier A. [1, 2] ; Costa, Luciano da Fontoura [3] ; Rodrigues, Francisco Aparecido [4]
Total Authors: 3
Affiliation:
[1] Indiana Univ, Sch Informat Comp & Engn, Bloomington, IN 47405 - USA
[2] Univ Sao Paulo, Fac Filosofia Ciencias & Letras Ribeirao Preto, Dept Comp & Matemat, Ribeirao Preto, SP - Brazil
[3] Univ Sao Paulo, Inst Fis Sao Carlos, Sao Carlos, SP - Brazil
[4] Univ Sao Paulo, Inst Ciencias Matemat & Comp, Dept Matemat Aplicada & Estat, Sao Carlos, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION; v. 83, APR 2020.
Web of Science Citations: 0
Abstract

The identification of the minimal set of nodes that maximizes the propagation of information is one of the most relevant problems in network science. In this paper, we introduce a new method to find the set of initial spreaders to maximize the information propagation in complex networks. We evaluate this method in assortative networks and verify that degree-degree correlation plays a fundamental role in the spreading dynamics. Simulation results show that our algorithm is statistically similar, regarding the average size of outbreaks, to the greedy approach in real-world networks. However, our method is much less time consuming than the greedy algorithm. (C) 2019 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 15/22308-2 - Intermediate representations in Computational Science for knowledge discovery
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 11/50761-2 - Models and methods of e-Science for life and agricultural sciences
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 15/50122-0 - Dynamic phenomena in complex networks: basics and applications
Grantee:Elbert Einstein Nehrer Macau
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 16/23698-1 - Dynamical Processes in Complex Network based on Machine Learning
Grantee:Didier Augusto Vega Oliveros
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 18/24260-5 - Spatiotemporal Data Analytics based on Complex Networks
Grantee:Didier Augusto Vega Oliveros
Support Opportunities: Scholarships abroad - Research Internship - Post-doctor