Diffusion model based on shared friends-aware independent cascade

Abstract

Due to the swift growth of social network and the large variety of its application, numerous research effort aims at predict or explain the information diffusion phenomenon and how the user behaviour changes according to the effect of social pressure. Applications like viral marketing, rumour controlling, and individual behaviour analysis are some areas where these researches are applied. Many models proposed to handle the problem of information diffusion. Such models mostly require disseminated probabilities to be assigned for each link in diffusion network. In this paper we address the problem of predicting the information diffusion cascade. The proposed model named "Shared Friends-Aware IC-Based Diffusion Model (SFA-ICBDM)" can be seen as extension to the well known diffusion model, Independent Cascade model(IC). (SFA-ICBDM) model make use of structural feature of diffusion network specifically the common friend and similarity in terms of behaviour among users as a probability of influencing among users, then predict the cascade of information dissemination. The experiment has been conducted using real world social network dataset (Meme Tracker). In sum, the proposed model has been compared with baseline model IC and related works, where it shows improvement over baseline and related works. In addition, some promising conclusions have been obtained.