A multiple information model incorporating limited attention and information environment

Abstract

Rapid development of intelligent information equipment accelerates the expansion of mobile social network. Speed of information spreading is gradually growing, there are lots of changes in the scale and mode of information spreading. But the basic communication network is not developed and not mature, when online information platforms breakdown sometimes it happens to be when important information appears. Therefore, the research is done to solve these occasion problems, help network information platform filter hot news and discuss the reason that hot news exists longer than other news in the Internet. In this paper, a multiple information propagation model incorporating both local information environment and people’s limited attention is proposed based on Susceptible Infected Recovered (SIR) model. Two new concepts are introduced into the model: heat rate and popular rate, to measure the local information influence power and people’s limited attention to information respectively, which are key factors determining node state transformation instead of fixed probability. In order to analyze the influence from limited attention, a situation is designed that several pieces of information are popular successively. The theoretical analysis shows that the early popular information gets more attention than the later popular information, and more attention makes it easier to spread. Besides, numerical simulation is conducted in both uniform network and scale-free network. The simulation results show that the early popular information is less vulnerable to the increase of information acceptance threshold and more sensitive to the decrease of information rejection threshold than the later popular information. Moreover, the model can also be used in the case of large amount of information transmission without adding too much complexity. Reasons are given in the research that the top hot news exists very much longer than the other ones, and latter news which have same influence as top news are hard to get the same focus. Meanwhile, results in the research can provide some ways for the other researches in the related fields. They also help related information platforms to filter and push news and referable strategies to maintain hot news.

Prediction of cross-border spread of the COVID-19 pandemic: A predictive model for imported cases outside China

“…SIR model was first proposed in 1926 and is mainly used to study the epidemic patterns of the black death and plague in London and Mumbai [ 20 ]. This model is classical kinetic transmission models that can be used for transmission studies not only of diseases [ 21 ] but for of information and computer viruses as well [ 22 , 23 ]. Drawing on the classical SIR model for infectious disease, We express the spread process of COVID-19 with the following differential equation: …”

Retraction: A multiple information model incorporating limited attention and information environment

“…The PLOS ONE Editors retract this article [ 1 ] because it was identified as one of a series of submissions for which we have concerns about peer review integrity and similarities across articles. These concerns call into question the validity and provenance of the reported results.…”