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

TL;DR

This paper introduces a two-phase diffusion model for viral marketing in online social networks, optimizing seed selection within a budget to maximize profit, and demonstrates significant profit improvements over traditional single-phase methods.

Contribution

It proposes a novel two-phase diffusion approach with theoretical analysis and solution methods, enhancing profit maximization in viral marketing under budget constraints.

Findings

Two-phase diffusion yields over 18% more profit than single-phase.

The approach achieves up to 40% profit increase in experiments.

The model's properties are rigorously proven and validated on real datasets.

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.