Spread Mechanism and Control Strategies of Rumor Propagation Model Considering Rumor Refutation and Information Feedback in Emergency Management

Abstract

The rumor-free equilibrium state and rumor-endemic equilibrium state are two symmetric descriptions of the status of a system. The constant spreading of rumors would affect the smooth operation of emergency management procedures and cause unnecessary social and economic loss. To reduce the negative effect of rumor propagation, in this paper, we introduce a compartmental model of rumor propagation, which considers the rumor refutation of public and information feedback. By deriving mean-field equations that describe the dynamics of the model, we use analytical and numerical solutions of these equations to investigate the threshold and dynamics of the model in both the closed system and open system. The results imply that the initial equilibrium point is not stable and there exists a rumor-free equilibrium point; in the open system, there exists a threshold beyond which rumors can spread; the stability of the initial equilibrium point is related to the threshold R0 = (φ*α)/μ, and there exists a rumor-endemic equilibrium point. The development process of rumor propagation can be divided into four stages: latent period, progressive period, intense period, and recession period. Under the influence of population, rumor spreading can exceed the threshold readily because the migration rate μ is usually less than the proportion of ignorants without critical ability φ, and the rumor spreading process in an open system presents a fluctuating development, the rumor would not disappear in this autonomous system. Based on the analysis, we propose some measures, such as providing open and efficient information queries and exchange platforms, etc.

SAR dynamical mechanism affected by diminishing marginal effect based on personal fashion psychology on multi-layer contacted network

“…In fact, personal willingness to adopt information is gradually increasing, but their enthusiasm for information is gradually decreasing. The phenomenon described can be explained by Diminishing Marginal Effects (DME) [30,31] in behavioral propagation. Diminishing Marginal Effects (DME) in behavioral propagation means that when person accumulates a message, he/she will gradually feel bored with this information.…”

Dynamical analysis and optimal control of the developed information transmission model

“…In terms of the impact of information on human society, it can be broadly classified as either positive or negative. For instance, knowledge transmission [ 1 , 2 ] and innovation capability transmission [ 3 ] are beneficial to social development, which constitutes positive information, whereas the spread of rumors [ 4 , 5 ] and computer viruses [ 6 – 8 ] constitutes negative information. It can be classified into two broad categories of information transmission channels: contact transmission [ 9 , 10 ] and network transmission [ 11 , 12 ].…”

“…The scholars mentioned above have conducted extensive research on transmitting various types of information via various channels, including the transmission of rumors [ 4 ], false information [ 5 ], competitive information [ 28 ] and malware [ 27 ]. Scholars who consider information transmission from the perspective of individuals are usually based on the attitude of transmission individuals to an event [ 22 – 24 , 31 , 32 ].…”

An effective ISDPR rumor propagation model on complex networks

“…Huo et al 20 joined true information spreader and social reinforcement to the model and gave some control strategies. Chen et al 21 considered the rumor refutation of public and information feedback, introduced a new rumor propagation model. Wang et al 22 introduced discernible mechanism and confrontation mechanism to quantify the level of people's cognitive abilities and the competition between the rumor and truth.…”