Cross-network propagation model of public opinion information and its control in coupled double-layer online social networks

Abstract

PurposeIn modern society, considering the multi-channel of public opinion information (public opinion) propagation and its strong influence on social development, it is necessary to study its propagation law and discuss the intervention strategy in online social networks (OSN).Design/methodology/approachFirst, a conceptual model of double-layer OSN was constructed according to their structural characteristics. Then, a cross-network propagation model of public opinion in double-layer OSN was proposed and discussed its spreading characteristics through numerical simulations. Finally, the control strategy of public opinion, especially the timing and intensity of intervention were discussed.FindingsThe results show that the double-layer OSN promotes the propagation of public opinion, and the propagation of public opinion in double-layer OSN has the characteristics of that in two single-layer OSN. Compared with the intervention intensity, the regulator should give the priority to the timing of intervention and try to intervene in the early stage of public opinion propagation.Practical implicationsThis study may help the regulators to respond to the propagation of public opinion in OSN more actively and reasonably.Originality/valueThis research has a deep comprehension of the cross-network propagation rules of public opinion and manages the propagation of public opinion.

Cross-platform opinion dynamics in competitive travel advertising: A coupled networks’ insight

“…This shows that under the influence of factors, such as the same travel advertising intensity, potential followers will not appear to be biased toward a certain network of travel advertising opinions. However, in a closed social network, individuals usually have a strong relationship with each other than in open social network, so they usually have a higher level of trust with each other (Li and Wang, 2022) and a higher level of confidence in others. Therefore, assume that ε 1 = 0.7, ε 2 = 0.5 and other parameters are as above.…”

“…Complex network theories and methods are widely used in dissemination dynamics ( Li et al, 2015 ; He et al, 2021 ). Existing research has shown that network topologies, such as WeChat and Facebook, have a critical impact on public opinion dissemination ( Zhang et al, 2018 ; Mandal et al, 2020 ; Li and Wang, 2022 ).…”

“…Users on such social media platforms have stronger relationships and a higher level of trust. Previous research has classified existing social media platforms into two major groups ( Li and Wang, 2022 ).…”

“…The connecting edge between networks A and B indicates that a user can have accounts in multiple social networks. Furthermore, in this coupled network, the correspondence between networks A and B is one-to-one; others are ignored ( Li and Wang, 2022 ). Nodes in networks A and B are connected at random.…”

“…However, in a closed social network, individuals usually have a strong relationship with each other than in open social network, so they usually have a higher level of trust with each other ( Li and Wang, 2022 ) and a higher level of confidence in others. Therefore, assume that ε 1 = 0.7, ε 2 = 0.5 and other parameters are as above.…”