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Modeling Competitive Marketing Strategies in Social Networks

Author

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  • Goel, Rahul
  • Singh, Anurag
  • Ghanbarnejad, Fakhteh

Abstract

A model is developed in which two players compete to spread information in the large network. Players choose their initial seed nodes simultaneously and the information is diffused according to Independent Cascade model (ICM). The main aim of the player is to choose the seed nodes such that they will spread its information to as many nodes as possible in a social network. Here we show and discuss how the rate of spreading of information as well as seed choosing depending on topological features play roles in information diffusion process. Any node in a social network will get influenced by none or one or more than one information. We also analyzed how much fraction of nodes in different compartment changes by changing the rate of spreading of information. Finally, a game theory model is developed to obtain the Nash equilibrium based on best response function of the players. This model is based on Hotelling’s model of electoral competition.

Suggested Citation

  • Goel, Rahul & Singh, Anurag & Ghanbarnejad, Fakhteh, 2019. "Modeling Competitive Marketing Strategies in Social Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 50-70.
    • Handle: RePEc:eee:phsmap:v:518:y:2019:i:c:p:50-70
    DOI: 10.1016/j.physa.2018.11.035
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    References listed on IDEAS

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    Cited by:

    1. Singh, Anurag & Arquam, Md, 2022. "Epidemiological modeling for COVID-19 spread in India with the effect of testing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    2. Ahmad, Amreen & Ahmad, Tanvir & Bhatt, Abhishek, 2020. "HWSMCB: A community-based hybrid approach for identifying influential nodes in the social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    3. Geng, Yang & Zhang, Yulin, 2020. "Platform launch in two-sided markets and users’ expectations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).

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