Dynamics of social contagions with local trend imitation

Zhu, Xuzhen; Wang, Wei; Cai, Shi-Min; Stanley, H. Eugene

doi:10.1038/s41598-018-25006-6

Cited by 20 publications

(16 citation statements)

References 34 publications

(54 reference statements)

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“…[3][4][5][6][7][8] Traditionally, the study of public opinion propagation was based on infectious disease models, such as SIS, SIR and SEIR models. [9][10][11] Wang explored the mechanisms of information propagation, including stifling, latent and forgetting mechanisms, to develop a refined SEIR model. 12 In addition, some researchers focus on influence of the media and social power on public opinion propagation.…”

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confidence: 99%

Network public opinion propagation model based on the influence of media and interpersonal communication

Zhang

Feng

Yang

2019

Int. J. Mod. Phys. B

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With the rapid development of the Internet, social media networks have become the primary platform for people to express their views. In addition, network public opinion has a considerable influence on society. Thus, considering the significant impact of online public opinion on society, it is necessary to study and analyze the propagation process for public opinion. In this study, we propose the Media and Interpersonal Relationship-SEIR (MI-SEIR) model based on the SEIR model. Our proposed model considers the impact of media transmission and interpersonal relationships on opinion propagation. Our MI-SEIR model divides the propagation nodes into three categories: support, neutral and opposition. There is a discussion mechanism between these nodes that represents the node’s viewpoint value evolution rule based on the node firmness, influence of nodes, quality of media coverage and parameters of infection. The state transition of nodes is decided based on the change of opinion value. Our simulation experimental results show that this model is more representative of the real propagation of online public opinion and is thus of practical significance for research and opinion analysis applications.

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confidence: 99%

Network public opinion propagation model based on the influence of media and interpersonal communication

Zhang

Feng

Yang

2019

Int. J. Mod. Phys. B

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“…Public opinion is formed in complex and interconnected networks [1] and can therefore be considered similar to other complex networks for research purposes [2][3][4][5]. e infectious disease model [6][7][8][9] is a common method of modeling complex networks, including public opinion networks.…”

Section: Introductionmentioning

confidence: 99%

Public Opinion Communication Model under the Control of Official Information

2021

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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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“…Based on complex network theory [33,34], regarding a user as a node and a connective relation as an edge [35], researchers have mined various underlying factors to investigate the information spreading mechanism and unveil the fundamental laws. Wide-ranging factors have been investigated, such as the initial seed size [36], clustering coe cient [37], community structure [38], temporal network [39], role of synergy [40,41], heterogeneous adoption thresholds [42], and limited imitation [43][44][45]. Additionally, information spreading on a multiplex network [46][47][48] has aroused the interest of researchers who perform numerous investigations about communication channel alternations on multiplex networks [49], heterogeneous behavioral adoption on multiplex networks [16], opinion competition on multiplex networks [50], e ect of multiple social networks on user awareness [51], social support for suppressing epidemics on multiplex networks [52], the interplay of social influence in multiplex networks [53], replicator dynamics on multiplex networks [54], etc.…”

Section: Introductionmentioning

confidence: 99%

Information Spreading on Weighted Multiplex Social Network

Zhu

et al. 2019

Complexity

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Information spreading on multiplex networks has been investigated widely. For multiplex networks, the relations of each layer possess different extents of intimacy, which can be described as weighted multiplex networks. Nevertheless, the effect of weighted multiplex network structures on information spreading has not been analyzed comprehensively. We herein propose an information spreading model on a weighted multiplex network. Then, we develop an edge-weight-based compartmental theory to describe the spreading dynamics. We discover that under any adoption threshold of two subnetworks, reducing weight distribution heterogeneity does not alter the growth pattern of the final adoption size versus information transmission probability while accelerating information spreading. For fixed weight distribution, the growth pattern changes with the heterogeneous of degree distribution. There is a critical initial seed size, below which no global information outbreak can occur. Extensive numerical simulations affirm that the theoretical predictions agree well with the numerical results.

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Dynamics of social contagions with local trend imitation

Cited by 20 publications

References 34 publications

Network public opinion propagation model based on the influence of media and interpersonal communication

Network public opinion propagation model based on the influence of media and interpersonal communication

Public Opinion Communication Model under the Control of Official Information

Information Spreading on Weighted Multiplex Social Network

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