Analysis of micro-blog diffusion using a dynamic fluid model

Abstract

Various methods on the display of dynamic information diffusion for social media have been proposed. Most of them use data mining approaches to explore the behaviors and interactions between users. Such approaches are unable to reveal the complex mechanism and the process of information diffusion. Lattice Boltzmann Method (LBM) models fluid behaviors at the microscopic scale, similar to the information diffusion in social media that is determined by the collective behavior of many personal retweeting of topics. We propose an information diffusion model inspired by the fundamental idea of LBM to analyze and simulate users’ communicating behaviors and processes in Micro-blogging. The micro-blog space is regarded as an artificial physical system with social phenomena such as micro-blog bursting. The macroscopic properties of the information diffusion model are explored to simulate and predict the trend of information diffusion for any specific topic. A novel visualization style mimicking fluid dynamics is proposed to help understand the scale of information diffusion and the popularity of a topic. The flow visualization based on the speed of information diffusion is useful in discovering typical information diffusion patterns for different types of topics in social networks. Comparing with other approaches, our approach provides more effective yet intuitive simulation.