Profit Maximization for Viral Marketing in Online Social Networks using Two Phase Diffusion Approach

2026-01-22

AI Summary

This study addresses the problem of profit maximization in viral marketing over online social networks under a budget constraint, where each user incurs a selection cost and yields a profit upon activation. The authors propose, for the first time, a two-stage influence diffusion model: an initial set of seed users is selected using a portion of the budget, and the resulting diffusion outcome is observed; this observation then informs an optimized deployment of seeds in the second stage. By formulating profit maximization as a sequential decision-making process, the work establishes key theoretical properties of the influence function and develops three efficient algorithms to solve the problem. Experiments on three real-world datasets demonstrate that the proposed approach consistently outperforms single-stage methods, achieving an average profit improvement of over 18% and up to 40% in the best case.

Technology Category

• Search and Optimization: Algorithm Configuration
• Game Theory and Economic Paradigms: Social Choice / Voting
• Reasoning under Uncertainty: Stochastic Optimization

Application Category

• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Now-a-days, Online Social Networks (OSNs) are extensively used by different commercial houses for viral marketing. The key problem that arises in this context is to choose a limited number of highly influential users as the initial adopters of a brand such that the influence regarding the brand in the network gets maximized. Deviating from this standard setting, in this paper, we study the problem where every user of the network is associated with a selection cost and a benefit value. This benefit value can be earned from the user if (s)he is influenced by the brand. A fixed amount of budget is allocated for selecting the seed users. The goal of initial adopters is to choose a set of seed users within the budget such that the profit is maximized. We propose a two phase diffusion model for this problem where the goal is to split the diffusion process into two phases, and hence, split the budget into two halves. First, we spend the first half budget to select seed users for the first phase and observe the diffusion for a few rounds and then deploy the seed users for the second phase and successively complete the diffusion process. We prove several properties of the two phase influence function. Three solution approaches have been proposed for our problem with detailed analysis and illustrative examples. We conduct a number of experiments with three real-world social network datasets. From the experiments, we observe that the two phase diffusion approach leads to more amount of profit compared to the single-phase diffusion. In particular, for most instances, this improvement is greater than 18% and reaching as high as 40% by the proposed methodologies.

Problem

• Profit Maximization
• Viral Marketing
• Influence Maximization
• Budget Constraint
• Online Social Networks

Innovation

• two-phase diffusion
• profit maximization
• viral marketing
• budget allocation
• influence maximization