Research on information dissemination on social networks based on edge-based compartmental theory

Abstract

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.

The information propagation mechanism of individual heterogeneous adoption behavior under the heterogeneous network

“…Based on Ref. [28], this study employs an edge-based compartmental (EBC) method for theoretical analysis of the model. By analyzing the variation in the number of individuals in different states in a multilayer network, the study provides a theoretical evaluation of the propagation mechanism in a heterogeneous adoption behavior network for the same information in a dual-layer setting.…”

Novel propagation phenomena: behaviors of local trend imitation on multiple limited contact networks

“…Based on references,we analyze the model theory using an edge-based compartmental (EBC) approach [31,32]. By contrasting the number changes of different state individuals in multiply layered network,we theoretically evaluate the information propagation mechanism of multiply layered network with limited contacts.…”