Viral marketing on social networks: An epidemiological perspective

Saumik Bhattacharya, Kumar Gaurav and Sayantari Ghosh

Physica A: Statistical Mechanics and its Applications, 2019, vol. 525, issue C, 478-490

Abstract: Omnipresent online social media nowadays has a constantly growing influence on business, politics, and society. Understanding these newer mechanisms of information diffusion is very important for deciding campaign policies. Due to free interaction among a large number of members, information diffusion on social media has various characteristics similar to an epidemic. In this paper, we propose and analyze a mathematical model to understand the phenomena of digital marketing with an epidemiological approach considering some realistic interactions in a social network. We apply mean-field approach as well as network analysis to investigate the phenomenon for both homogeneous and heterogeneous models, and study the diffusion dynamics as well as equilibrium states for both the cases. We explore the parameter space and design strategies to run an advertisement campaign with substantial efficiency. Moreover, we observe the phenomena of bistability, following which we estimate the necessary conditions to make a campaign more sustainable while ensuring its viral spread.

Keywords: Viral marketing; Epidemiological model; Bistability; Mean-field analysis; Graph-theoretical treatment; Online social networks (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:525:y:2019:i:c:p:478-490

DOI: 10.1016/j.physa.2019.03.008

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