Mobile Networks and Applications

, Volume 23, Issue 4, pp 717–722 | Cite as

Information Diffusion Model Based on Social Big Data

  • Dawei Jin
  • Xiao Ma
  • Yin ZhangEmail author
  • Haider Abbas
  • Han Yu


Users can access Weibo, a widely used social network platform, through mobile clients or PCs at any time for social interaction. This paper describes an information diffusion model based on the Weibo platform, which is used to measure information diffusion based on the extent of reposting on Weibo. First, the information diffusion of a Weibo post created in the evening is analyzed, and a quantitative analysis is conducted on the information diffusion within a particular period of time of night, targeting user behavior characteristics during that time, to further improve the accuracy of the model. Moreover, an information diffusion model based on superposition theory is proposed with respect to the participation of key users in the information diffusion process.


Information diffusion Social network Superposition models Information management Big data analytics Information delivery 



This work was supported by the National Social Science Foundation of China under grant No. 13CTJ003 and by the China Postdoctoral Science Foundation under grant No. 2014M562025.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Dawei Jin
    • 1
  • Xiao Ma
    • 1
  • Yin Zhang
    • 1
    • 2
    Email author
  • Haider Abbas
    • 3
    • 4
  • Han Yu
    • 1
  1. 1.School of Information and Safety EngineeringZhongnan University of Economics and LawWuhanChina
  2. 2.State Key Laboratory for Novel Software TechnologyNanjing UniversityNanjingChina
  3. 3.National University of Sciences and TechnologyIslamabadPakistan
  4. 4.Florida Institute of TechnologyMelbourneUSA

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