Diversified viral marketing: The power of sharing over multiple online social networks

Dawood Al Abri*, Shahrokh Valaee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The popularity of online social networks (OSNs) makes them attractive platforms to advertise products. Previous work on marketing in OSNs utilized older diffusion models that do not capture the interactions of modern OSNs and hence there is a need to develop a model that accounts for the interactions that occur in current OSNs. In this paper, we introduce a new model for information flow in online social networks that captures the sharing behavior exercised by users when they pass information from one online social network to their social circles in another network. We, then, formulate a problem of maximizing the marketing reach where the diversity of users’ other social networks is taken as a constraint. We also propose a greedy algorithm to solve the aforementioned optimization problem. Numerical results show that the proposed algorithm achieves better results than algorithms that are based on classical degree centrality metric and with comparable running time.

Original languageEnglish
Article number105430
JournalKnowledge-Based Systems
Volume193
DOIs
Publication statusPublished - Apr 6 2020
Externally publishedYes

Keywords

  • Advertisement
  • Diffusion model
  • Influence maximization
  • Social networks
  • Viral marketing

ASJC Scopus subject areas

  • Management Information Systems
  • Software
  • Information Systems and Management
  • Artificial Intelligence

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