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A Priority-Based Ranking Approach for Maximizing the Earned Benefit in an Incentivized Social Network

  • Suman BanerjeeEmail author
  • Mamata Jenamani
  • Dilip Kumar Pratihar
  • Abhinav Sirohi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 940)

Abstract

Given a social network of users represented as a directed graph with edge weight as diffusion probability, selecting a set of highly influential users for initial activation to maximize the influence in the network is popularly known as the Social Influence Maximization Problem. In this paper, we study a different and more practical variant of this problem, where each node is associated with a selection cost which signifies the incentive demand if it is included in the seed set; a fixed budget that can be spent for the seed set selection process; a subset of the nodes designated as the target nodes and each of them is associated with a benefit value that can be earned by influencing the corresponding user; and the goal is to choose a seed set for maximizing the earned benefit within the allocated budget. For this problem, we develop a priority based ranking methodology having three steps. First, marking the effective nodes for the given target nodes; second, priority computation of the effective nodes and the third is to choose the seed nodes based on this priority value within the budget. We implement the proposed methodology with two publicly available social network datasets and observe that the proposed methodology can achieve \(0.03 \text { to } 1.14\) times more benefit compared to the baseline methods without much increase in computational burden.

Keywords

Social network Influence Maximization Earned benefit Influence probability Effective nodes 

Notes

Acknowledgment

Authors’ want to thank Ministry of Human Resource and Development (MHRD), Government of India, for sponsoring the project E-business Center of Excellence under the scheme of Center for Training and Research in Frontier Areas of Science and Technology (FAST), Grant No. F.No.5-5/2014-TS.VII.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Suman Banerjee
    • 1
    Email author
  • Mamata Jenamani
    • 1
  • Dilip Kumar Pratihar
    • 1
  • Abhinav Sirohi
    • 1
  1. 1.Indian Institute of Technology KharagpurKharagpurIndia

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