The study of the mechanism of information dissemination on social networks has important practical significance for information dissemination prediction. Aiming at the impact of the reinforcement effect derived from nonredundant information memory on information dissemination, this paper proposes a susceptible–exposed–adopted–recovered (SEAR) information dissemination model. This model considers the reinforcement effect of nonredundant information memory characteristics, and is theoretically analyzed based on an edge-based compartmental theory. This model reveals the law of individual information transmission in real society and better explains the process of information transmission. The simulation results show that the reinforcement effect of nonredundant information memory has a significant impact on information dissemination. The stronger the reinforcement effect, the greater the final behavior adoption size, that is, the wider the scope of information dissemination. The theoretical prediction is basically consistent with the simulation results, which shows that the method of edge-based compartmental theory has a specific validity. In addition, changing the individual’s “on” threshold, the individual’s stability threshold, the proportion of individuals in the initial adopted state, and the heterogeneity of degree distribution can make the final behavior adoption size increase linearly or vertically with the probability of information transmission.
Studying the mechanism of information dissemination in Social Internet of Things (SIoT) has practical significance for real-time information control and scientific management decision-making in real world. Aiming at the problem of how to realize the information interaction between people, people and things, and things and things in SIoT, we propose a cloud-edge collaborative dynamic information dissemination model (CCDIDM) for SIoT. Firstly, considering the interactive influence of information dissemination between individual users, between IoT devices, and between users and devices, the coupling relationship between nodes is established. Based on the theory of dissemination dynamics, the information propagation process between coupled nodes of SIoT is analyzed, and the efficient interactive dissemination of information is simulated. Theoretical analysis of the model is carried out, and the information dissemination threshold and the stability of the equilibrium point are deduced. Simulation results are consistent with the theoretical analysis, demonstrating that CCDIDM can describe information dissemination. Simultaneously, it was found that, stronger the perception awareness of individual users, smaller the scale of information dissemination. In addition, the influence of various parameters on the scale of information dissemination is verified. Adjusting the size of such parameters can promote or inhibit the dissemination of information.
The rapid development of Internet technology has facilitated the dissemination of information that can threaten national security and public health, and effectively controlling the process of public opinion communication is an important topic in contemporary social network research. This paper establishes an official information-controlled public opinion propagation (OI-SEIR) model based on the delay, latency, and conversion of public opinion communication under the control of official information. According to the influence and importance of the network nodes, we theoretically derive the attitude conversion probability of the nodes, making the model more in line with the actual situation. Through actual cases, we analyzed the important influence of official information on the public opinion communication process and provided a theoretical basis for the government and relevant departments to supervise and correctly guide the public opinion network, which has certain practical significance.
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