A Stochastic Information Diffusion Model in Social Networks Based on SIR Epidemic Model

Abstract

Social networks are an important infrastructure for information, the paper present a information diffusion model with random perturbation in social networks, which is based on SIR deterministic epidemic diseases. We prove that there exists a unique nonnegative solution to the stochastic information diffusion model for any positive initial value, investigate the stochastic asymptotic behavior of the information diffusion model, give the stability condition by the construction of the Lyapunov function, i.e. the conditions of the information diffusion will die out and be persistent in social networks.

Social Trust-based Blockchain-enabled Social Media News Verification System

“…The consensus protocol creates a system of collective agreements [Delmi 2018], which regulates the management of transaction blocks, while ensuring the integrity of the information stored in them [Xia et al 2019]. One of the commonly used consensus protocol methods is the Proof of Stake (PoS).…”

“…They conduct numerical analyses and simulated a news spreading model that was designed based on the Poisson distribution theorem, the Susceptible-Infected-Recovered (SIR) epidemic model and the smart contract protocol. Blockchain technology has the ability to build trust in a safe and decentralized system [Xia et al 2019] and can encourage trust from the edge of the communications chain, the social media users, allowing them to contribute by reporting false news. Therefore, many other unsuspecting users can be conscripted to selectively read and spread news.…”