Online social networks are overwhelmed with information spreading, phenomena whose underlying mechanisms require deeper analysis. In this paper, we introduce the direct credibility among nodes, a parameter that takes into account news trustworthiness. We exploit this amount into a well-known epidemic model to study the news diffusion process and to discover which elements affect the decision of individuals to propagate or not the news. In addition, we also consider how credibility evolves over time, in particular how news spreading process and nodes credibility assessment mutually influence themselves. Simulations on synthesized social networks show that the proposed approach seems a good starting point to define a realistic news spreading model.

A trust-based news spreading model

Carchiolo, V.;Longheu, A.;Malgeri, M.;Mangioni, G.;Previti, M.
2018

Abstract

Online social networks are overwhelmed with information spreading, phenomena whose underlying mechanisms require deeper analysis. In this paper, we introduce the direct credibility among nodes, a parameter that takes into account news trustworthiness. We exploit this amount into a well-known epidemic model to study the news diffusion process and to discover which elements affect the decision of individuals to propagate or not the news. In addition, we also consider how credibility evolves over time, in particular how news spreading process and nodes credibility assessment mutually influence themselves. Simulations on synthesized social networks show that the proposed approach seems a good starting point to define a realistic news spreading model.
978-3-319-73197-1
978-3-319-73198-8
Applied Mathematics; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/361761
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