Abstract
The number of potential participants in information diffusion is dynamically changing, and the topological structure of a real social network is affected by environment noise. In this paper, a stochastic information diffusion model considering both population perturbation and connectivity variation has been proposed. For the model on homogeneous network, we show the existence and uniqueness of the global positive solution and give a sufficient condition of extinction of information. A series of numerical simulations on Watts-Strogatz (WS) network, Barabasi-Albert (BA) network and real-world Facebook network have been conducted to verify the theoretical analysis and evaluate the sensitivity of the proposed model to relevant parameters. We find that both population perturbation and connectivity variation have great impacts on information diffusion process. In general, the connectivity variation noise promotes the spread of information, and the population perturbation noise corresponding to I-infected individuals inhibit the spread of information. In the case of large noise intensity, the population perturbation noise corresponding to I-infected individuals plays a decisive role compared with the connectivity variation noise.
Highlights
In the past decades, the researches of complex network have been widely reported [1]–[5]
For stochastic differential equations (SDE) model on homogeneous network, in order to analyze the properties of solutions and prove the steady state, we show the existence and uniqueness of the global positive solution and give a sufficient condition of extinction of information
We conduct a series of numerical simulations on synthetic networks and real-world Facebook network to verify the theoretical analysis and evaluate the sensitivity of the proposed model to relevant parameters
Summary
The researches of complex network have been widely reported [1]–[5]. Sun et al [24] proposed a competitive diffusion model to describe the diffusion processes of two types of information in social networks These models are ordinary differential equations (ODE) that based on mean-field theory and percolation theory. Stochastic differential equations (SDE) models have been widely used in researches of modeling epidemic with noise perturbation, and many scholars showed that environmental noise has great influence on epidemic dynamics [28]–[31]. The size of a real social network is always non-fixed, which indicates that the number of potential participants in information diffusion is dynamically changing. Inspired by the above researches in population and epidemic dynamics, we introduce population stochasticity into model via the technique of parameter perturbation.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
