Social networks are hugely used to spread information, and the understanding of mechanisms and behaviours leading the news diffusion process still deserves a major attention. In this paper we introduce the direct credibility among nodes, a parameter that takes into account their past interactions. We exploit this amount into a well-known epidemic model to analyze the diffusion of the news and to identify the elements that influence the decision of individuals to propagate or not the news. Simulations on synthesized social networks show that the proposed approach represents a good starting point towards the definition of a realistic news spreading model.
|Titolo:||Introducing credibility to model news spreading|
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|