Rumour propagation considering the active inquiry factor on social media networks. (2018)

• Record Type: Journal Article
• Authors: Wang, Jing; Wang, Ya-Qi; Li, Min
• Is Part Of: International journal of innovative computing and applications. Volume 9:Number 2(2018)
• Page Start: 107
• Page End: 115
• Publication Date: 2018
• Subjects: rumour propagation -- active inquiry -- susceptible-infected-removed -- SIR model -- social media; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

In this paper, considering the influence of the active inquiry factor, the dynamical behaviours of rumour spreading on social media networks is investigated by means of mean-field theory. The mean-field equations of two cases of link global addition and link local addition are derived to describe the propagation process of susceptible-infected-removed (SIR) rumour model, separately. Theoretical analysis shows that, considering the influence of the active inquiry factor, the higher the proportion that new links are added into the networks, the smaller the propagation critical threshold, the faster the transmission velocity of rumours. It is also found that with the increase of the number of new addition links, the number of nodes that finally accept rumours also increases. In addition, compared with the link global addition case, the number of nodes that are finally infected by rumours in the link local addition case is clearly reduced. Numerical simulations have confirmed the theoretical results.