The susceptible-infected-recovered (SIR) model for viral marketing

Ismail, Siti Suhaila; Akil, Ku Azlina Ku; Chulan, Majdah; Sharif, Noorzila

doi:10.1063/1.5012164

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…The Susceptible-Infected-Recovered (SIR) model [1] is a popular diffusion model for assessing the effectiveness of centrality measures. It can be used to model a wide range of real-world scenarios such as viral marketing and cyberattacks and has numerous implications [3,12,23,39]. At first, one ranks the nodes in the decreasing order of their centrality value.…”

Section: Susceptible-infected-recovered Modelmentioning

confidence: 99%

Comparative evaluation of community-aware centrality measures

Rajeh,

Savonnet,

Leclercq

et al. 2022

Preprint

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Influential nodes play a critical role in boosting or curbing spreading phenomena in complex networks. Numerous centrality measures have been proposed for identifying and ranking the nodes according to their importance. Classical centrality measures rely on various local or global properties of the nodes. They do not take into account the network community structure. Recently, a growing number of researches have shifted to community-aware centrality measures. Indeed, it is a ubiquitous feature in a vast majority of real-world networks. In the literature, the focus is on designing community-aware centrality measures. However, up to now, there is no systematic evaluation of their effectiveness. This study fills this gap. It allows answering which community-aware centrality measure should be used in practical situations. We investigate seven influential communityaware centrality measures in an epidemic spreading process scenario using the Susceptible-Infected-Recovered (SIR) model on a set of fifteen real-world networks. Results show that generally, the correlation between community-aware centrality measures is low. Furthermore, in a multiple-spreader problem, when resources are available, targeting distant hubs using Modularity Vitality is more effective. However, with limited resources, diffusion expands better through bridges, especially in networks with a medium or strong community structure.

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Section: Susceptible-infected-recovered Modelmentioning

confidence: 99%

Comparative evaluation of community-aware centrality measures

Rajeh,

Savonnet,

Leclercq

et al. 2022

Preprint

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“…The highly networked society has amplified the potential of viral marketing. Scholars have proposed various communication models(e.g., STEPP Model) to describe the process of spreading marketing messages on social networks in order to gain insight into the inner workings of viral marketing and propose effective viral marketing strategies accordingly [7][8][9][10].…”

Section: Literature Reviewmentioning

confidence: 99%

The Myth of STEPP Model: Based on A Framework of Dyson

Guo¹

2022

BCPBM

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The Internet is leading the era of virtual economy, the traditional marketing model based on publicity and promotion is gradually showing many drawbacks, and the network marketing represented by viral marketing is gradually becoming the mainstream model, which can have a subtle impact on consumer behavior. Accordingly, this has put forward requirements for the innovation of enterprise marketing models and methods. This paper uses viral marketing theory as the basis of research, and combines a renowned business framework, Dyson Co., Ltd, and this research aims to deliver readers a fundamental view of novel marketing strategies to have products or ideas go viral even though the traditional marketing strategy is classic and wise, it does not meet temporary market demands enough.

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“…Once the infected forgets to share a message or is tired of passing the message, she belongs to the recovered compartment [11]. This susceptible-infected-recovered (SIR) model described above has been widely accepted to study the viral marketing strategy [12], [13]. However, the SIR model assumes that the virus can be life-long immunized, which cannot be guaranteed for many diseases [14].…”

Section: A Justification For Using Sirs Modelmentioning

confidence: 99%

Optimal Control for Heterogeneous Node-Based Information Epidemics Over Social Networks

Liu

Buss

2020

IEEE Trans. Control Netw. Syst.

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In this paper, we investigate the optimal control problems of heterogeneous node-based information epidemics. A node-based Susceptible-Infected-Recovered-Susceptible (SIRS) model is introduced to describe the information diffusion processes taking into account heterogeneities in both network structures and individual characters. Aiming at guiding information dissemination processes towards the desired performance, we propose an optimal control framework with respect to two typical scenarios, i.e., impeding the spread of rumors and enhancing the spread of marketing or campaigning information. We prove the existence of the solutions and solve the optimal control problems by Pontryagin Maximum Principle and forward-backward sweep method. Moreover, numerical experiments validate the using of the node-based SIRS model by comparing with the exact 3 N-state Markov chain model. The effectiveness of the proposed control rules are demonstrated on both models. Further discussion on the influence of the parameters provides insights into the strategies of guiding information diffusion processes.

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The susceptible-infected-recovered (SIR) model for viral marketing

Cited by 5 publications

References 4 publications

Comparative evaluation of community-aware centrality measures

Comparative evaluation of community-aware centrality measures

The Myth of STEPP Model: Based on A Framework of Dyson

Optimal Control for Heterogeneous Node-Based Information Epidemics Over Social Networks

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