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Analysis of micro-blog diffusion using a dynamic fluid model

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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.

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Acknowledgments

This paper was supported in part by Natural Science Foundation of China under Grants 61272199, and the National High-tech R&D Program of China (863 Program) under Grant no. SS2015AA010504, and Innovation Program of Shanghai Municipal Education Commission under Grants 12ZZ042, and the Specialized Research Fund for the Doctoral Program of Higher Education under Grants 20130076110008, and Shanghai Collaborative Innovation Center of Trustworthy Software for Internet of Things under Grant no. ZF1213. The authors would like to thank Weining Qian and Qunyan Zhang for providing the data on Sina micro-blog. The authors also thank the anonymous reviewers for their insightful comments that have helped us to improve the presentation of the paper.

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Authors and Affiliations

  1. Software Engineering Institute, East China Normal University, Shanghai, 200062, China

    Yuhua Liu & Changbo Wang

  2. College of Computer Science and Technology, Soochow University, Suzhou, 215006, China

    Peng Ye

  3. Department of Computer Science, University of Texas at Dallas Richardson, Richardson, TX, 75080, USA

    Kang Zhang

Authors
  1. Yuhua Liu
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  2. Changbo Wang
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  3. Peng Ye
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  4. Kang Zhang
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Correspondence to Changbo Wang.

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Liu, Y., Wang, C., Ye, P. et al. Analysis of micro-blog diffusion using a dynamic fluid model. J Vis 18, 201–219 (2015). https://doi.org/10.1007/s12650-015-0277-y

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